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Motivation to call police: The exploration of racialand risk averse motivationAlivia Lauren ZubrodUniversity of Northern Iowa

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Copyright by

ALIVIA LAUREN ZUBROD

2019

All Rights Reserved

MOTIVATION TO CALL POLICE: THE EXPLORATION OF RACIAL AND RISK

AVERSE MOTIVATION

An Abstract of a Thesis

Submitted

In Partial Fulfillment

of the Requirements for the Degree

Master of Arts

Alivia Lauren Zubrod

University of Northern Iowa

July 2019

ABSTRACT

When calls are made to the police, the magnitude of their impact is often overlooked.

When calls are made to the police and there is no crime, police resources, time, and

energy could be wasted (Sampson, 2002); however, when no call is made to the police

and there is a crime, human lives could be put in danger (e.g., Felson, Messner, Hoskin,

& Deane, 2002). Based on highly publicized news reports, it appears that being a racial

minority is enough motivation to call the police in some situations (e.g., napping or

humanitarian work; Griggs, 2018; Williams, 2018b). Aversive racism theory (Gaertner &

Dovidio, 1986) suggests that when racial prejudice can be rationalized to another factor

aside from race, then aversive racists may act in discriminatory ways. Thus, a person may

rationalize a call to the police based on someone yelling rather than their skin color. Risk

averse motivation (Kahneman & Tversky, 1982) suggests that individuals prefer a certain

choice compared to an uncertain choice. Thus, individuals who call the police could be

risk averse and choose to call the police to provide a sense of certainty in an uncertain

situation. In this study, I tested these two possible motivations using an ambiguous risk

scenario. Participants (N = 295) from an online data collection platform read a scenario

and reported their likelihood to call the police, whether they would call the police

(yes/no), and whether they agreed with someone else’s decision to call the police based

on the scenario. Then participants completed a risk perception scale. The race of the

perceived suspect was not influential in the reported likelihood to call the police, whether

a participant would call the police, or their agreement with someone else’s decision to

call the police; however, participants who were risk averse, as well as women and

political conservatives reported a greater likelihood to call the police, were more likely to

report that they would call the police, and agreed more with someone else’s decision to

call the police. Despite the results of the current study, there are still news reports that

suggest racial minorities are the source of motivation for calls to the police. Thus, race as

a potential motivation to call the police should be continued to be examined.

Keywords: motivation, race, aversive racism, risk averse, police

MOTIVATION TO CALL POLICE: THE EXPLORATION OF RACIAL AND RISK

AVERSE MOTIVATION

A Thesis

Submitted

In Partial Fulfillment

of the Requirements for the Degree

Master of Arts

Alivia Lauren Zubrod

University of Northern Iowa

July 2019

ii

This Study by: Alivia Lauren Zubrod

Entitled: Motivation to Call Police: The Exploration of Racial and Risk Averse

Motivation

has been approved as meeting the thesis requirement for the

Degree of Master of Arts

___________ ____________________________________________________

Date Dr. Jiuqing Cheng, Chair, Thesis Committee

___________ ____________________________________________________

Date Dr. Helen C. Harton, Thesis Committee Member

___________ ____________________________________________________

Date Dr. Matthew Makarios, Thesis Committee Member

___________ _____________________________________________________

Date Dr. Jennifer J. Waldron, Dean, Graduate College

iii

DEDICATION

For my Uncle John, I miss you every day.

iv

TABLE OF CONTENTS

PAGE

LIST OF TABLES ............................................................................................................ vii

LIST OF FIGURES ......................................................................................................... viii

CHAPTER 1. INTRODUCTION ...................................................................................... 1

Decision to Call the Police .............................................................................................. 3

Racial Differences in Calling the Police ......................................................................... 6

Racial Differences in Arrest Rates .................................................................................. 7

Racial Differences in Incarceration Rates ....................................................................... 8

Aversive Racism Theory ................................................................................................. 9

Risk Averse Motivation ................................................................................................ 11

Other Explanations: Gender and Political Orientation .................................................. 15

CHAPTER 2. CURRENT STUDY ................................................................................. 16

Research Questions.................................................................................................... 18

Exploratory Questions ............................................................................................... 20

CHAPTER 3. METHOD .................................................................................................. 22

Pretest ............................................................................................................................ 22

Participants .................................................................................................................... 23

Procedure ....................................................................................................................... 25

Variables and Measures ................................................................................................ 26

Evaluation Questions ................................................................................................. 26

Manipulation Check .................................................................................................. 27

30-Item Domain-Specific Risk-Taking Scale (DOSPERT) ...................................... 27

Demographic Questions ............................................................................................ 28

Additional End-of-Study Questions .......................................................................... 28

CHAPTER 4. RESULTS .................................................................................................. 30

Exclusion Criteria .......................................................................................................... 30

Assumptions .................................................................................................................. 31

Plan for Analysis ........................................................................................................... 32

v

Dependent Variables Examination ................................................................................ 35

Evaluations of the Scenario, Police Involvement, and the Suspect ........................... 37

Hierarchical Linear Regression: Likelihood to Call Police........................................... 42

Research Question 1 .................................................................................................. 43



Examining Gender: Linear Regression ...................................................................... 45

Examining Political Orientation: Linear Regression ................................................. 47

Logistic Regression: Call Police ................................................................................... 49




Examining Gender: Logistic Regression (Call Police) .............................................. 53

Examining Political Orientation: Logistic Regression (Call Police) ......................... 56

Logistic Regression: Someone Else Call Police ........................................................... 59




Examining Gender: Logistic Regression (Someone Else Call Police) ...................... 62

Examining Political Orientation: Logistic Regression (Someone Else Call Police) . 67

Mediation Analysis ....................................................................................................... 72

CHAPTER 5. DISCUSSION ........................................................................................... 74

Summary of Results................................................................................................... 74

Race ........................................................................................................................... 74

Risk Perception .......................................................................................................... 77

Gender ....................................................................................................................... 77

Political Orientation ................................................................................................... 78

Limitations and Future Research ............................................................................... 80

Implications ............................................................................................................... 81

vi

Conclusion ................................................................................................................. 83

REFERENCES ................................................................................................................. 84

APPENDIX A: AMBIGUOUS RISK SCENARIO ......................................................... 96

APPENDIX B: INFORMED CONSENT ......................................................................... 97

APPENDIX C: DEBRIEFING FORM ............................................................................. 99

APPENDIX D: EVALUATION QUESTIONS ............................................................. 100

APPENDIX E: MANIPULATION CHECK .................................................................. 101

APPENDIX F: 30-ITEM DOSPERT SCALE ................................................................ 102

APPENDIX G: DEMOGRAPHICS ............................................................................... 104

APPENDIX H: ADDITIONAL END-OF-STUDY QUESTIONS ................................ 106

vii

LIST OF TABLES

TABLE PAGE

1 Demographic Characteristics .................................................................................24

2 N of Cases of Data Removed from Analyses ........................................................31

3 Correlations of the Dependent Variables ...............................................................37

4 Dichotomous Choice Item Response .....................................................................37

5 Correlations of the Evaluation Questions and the Dependent Variables ...............41

6 Correlations of the Variables by Condition ...........................................................42

7 The Likelihood to Call Police ................................................................................44

8 The Influence of Gender on the Likelihood to Call Police ....................................46

9 The Influence of Political Orientation on the Likelihood to Call Police ...............48

10 Correlation Matrix: The Choice to Call Police ......................................................50

11 The Choice to Call Police ......................................................................................52

12 Correlation Matrix: Gender and the Choice to Call Police ....................................54

13 The Influence of Gender on the Choice to Call Police ..........................................55

14 Correlation Matrix: Political Orientation and the Choice to Call Police ...............57

15 The Influence of Political Orientation on the Choice to Call Police .....................58

16 Correlation Matrix: Someone Else’s Decision to Call Police ................................59

17 Someone Else’s Decision to Call Police ................................................................61

18 Correlation Matrix: Gender and Someone Else’s Decision to Call Police ............63

19 The Influence of Gender on the Agreement with Someone Else’s Decision to Call

Police......................................................................................................................65

20 Correlation Matrix: Political Orientation and the Agreement with Someone Else’s

Decision to Call Police...........................................................................................68

21 The Influence of Political Orientation on the Agreement with Someone Else’s

Decision to Call Police...........................................................................................70

viii

LIST OF FIGURES

FIGURES PAGE

1 Interaction between Gender and Risk Perception on the Agreement with Someone

Else’s Decision to Call the Police ..........................................................................66

2 Interaction between PO and Risk Perception on the Agreement with Someone

Else’s Decision to Call the Police ..........................................................................71

3 Mediation Model ....................................................................................................73

1

CHAPTER 1.

INTRODUCTION

"Who ya gonna call?"(Parker, 1984) has been asked in popular media, but perhaps

the more important and often ignored question is, "When ya gonna call?” Each year,

about 240 million calls are made to 911 (“9-1-1 Statistics,” 2017). There are numerous

reasons to call 911, such as to report a violent crime1 (45%), a serious violent crime2

(51%), or a property crime 3 (36%; Morgan & Truman, 2018). Thus, the decision to call

the police4 is more complex than just dialing numbers. When calls are made to the police

and there is no actual crime (e.g., misuse of 911, non-emergency situations), this can take

away valuable resources from individuals who need police services (Sampson, 2002);

however, not calling the police when there is a crime could potentially endanger human

life (e.g., Felson et al., 2002). Thus, the decision to call the police has social and

emotional consequences (Greenberg, Wilson, Ruback, & Mills, 1979). Further, there are

many potential factors that may influence the decision to call the police.

One potential motivation to call the police could be related to race. In 2018, an

Oregon state representative was canvassing door-to-door in her district when the police

were called because of her “strange behavior” (i.e., using her cell phone after visiting

each house; Archie & Smith, 2018). In Ohio, the police confronted a 12-year-old

landscaping entrepreneur who mistakenly mowed a lawn next to a house of a client

1 Violent crime includes rape or sexual assault, robbery, aggravated assault, simple assault, and serious

violent crime; thus, serious violent crime is a subset of violent crime (Morgan & Truman, 2018). 2 Serious violent crimes includes rape or sexual assault, robbery, and aggravated assault (Morgan &

Truman, 2018). 3 Property crime includes household burglary, theft, and motor vehicle theft (Morgan & Truman, 2018). 4 Throughout this paper, the terms call 911, report crime, and call police are used interchangeably.

2

(Williams, 2018a). The police also confronted a California Samaritan who was helping a

local homeless man (Williams, 2018b). A student napping in a dorm common space

(Griggs, 2018), customers not ordering anything at a coffee shop and leaving (McCleary

& Vera, 2018), and friends simply leaving an Airbnb also had police called on them

(Criss & Vera, 2018). Additionally, the police confronted a man walking with a duffel

bag at the University of Massachusetts at Amherst (UMass; Jaschik, 2018), a woman

looking “out of place” at Smith College (Whitford, 2018), and a man at a local dog park

(Fieldstadt, 2019). In all these incidents, the alleged police suspects were black and

innocent: A black state representative, a black child, a black Samaritan, a black student,

two black potential coffee shop customers, three black friends, an employed black man at

UMass, a black student at Smith College, and a black man who took his dog to a dog

park. From all these examples, it appears that the presence of a racial minority is

motivation enough to call the police for some people. Thus, there appears to be potential

prejudice and discrimination toward racial minorities when calls are made to the police.

The current study will examine two possible theories that may help explain why

people call the police. People may call the police because of racial bias, or people may

call the police because of the perceived risk regarding a given situation. Aversive racism

theory (Gaertner & Dovidio, 1986) suggests that individuals generally support egalitarian

values; however, aversive racists discriminate when bias can be attributed to another

factor besides race (e.g., a woman looking “out of place;” Dovidio & Gaertner, 2000;

Whitford, 2018). Alternatively, the decision to call the police could have nothing to do

with discrimination and prejudice and could be motivated by other factors, such as risk

3

averse motivation. Risk averse motivation (Kahneman & Tversky, 1982) is based off

gambling research and is characterized as human preference in decision making

(Kahneman & Tversky, 1982; Zhang, Brennan, & Lo, 2014). A risk averse decision is the

tendency to prefer the certain option compared to the uncertain option (Paulsen, Platt,

Huettel, & Brannon, 2012). Thus, in an ambiguous or perceived suspicious situation,

calling the police, regardless of race, could provide a sense of certainty. In the next

sections, I will further discuss the decision to call the police, disparities regarding the

criminal justice system, aversive racism theory, and risk averse motivation.

Decision to Call the Police

There are many reasons to call the police. Although this paper focuses on calls

made to the police in the United States for possible crime situations, there are other

reasons someone may choose to call the police (e.g., non-crime related emergencies; to

seek help from police; participation in an anti-crime program). Further, police contact is

not always initiated by a civilian, but could be police-initiated contact. For instance, of

53.5 million individuals who experienced contact with the police in 2015, about 11% of

those contacts were police initiated (Davis, Whyde, & Langton, 2018).

Of the U.S. population, 16 and older, overall contact with the police has decreased

from 26 to 21% since 2011 (Davis et al., 2018). Although there has been an overall

decrease in police and citizen contact in the United States, it is important to understand

and examine the decision to call the police.

4

Within previous psychological literature, the decision to call the police has

focused on bystander intentions inspired by the Kitty Genovese5 case. The decision to

call the police creates complex feelings, which generate a sense of conflict from both

humanitarian and fear-based emotions in individuals (Darley & Latané, 1968). Despite

the complexity of helping behavior, Latané and Darley (1970) suggest that there are a

series of decisions an individual must make before deciding to intervene and act in an

emergency situation. First, the bystander must notice that a situation is happening. Once

the bystander is aware of the event, the bystander must interpret the event as an

emergency. If the bystander concludes that something is indeed wrong, the bystander

must decide their personal responsibility in the decision to act upon the situation. If the

bystander decides to act upon the situation (i.e., help), the bystander must decide what

form of help to give (e.g., call 911, provide direct assistance). Lastly, the bystander must

decide how to implement the plan of action (e.g., use a cell phone). When a bystander is

confronted with an emergency situation, depending on the series of choices made, the

bystander will intervene or not in an emergency situation (Latané & Darley, 1970).

There are other determinants that can influence how bystanders perceive these

decisions, such as social influence. Social impact theory suggests that decision to call the

police or not could be exacerbated by the influence of other individuals based on the

strength (i.e., status of others), immediacy (i.e., closeness of others), and the number of

people there are in a given situation (Latané, 1981). Research has shown that social

5 In 1964, Kitty Genovese was stabbed to death outside of her apartment building, in a New York

residential area. Although no one came to her aid directly, it was reported later that there were calls made to

the police (Kassin, 2017). It has been reported that 38 of her neighbors heard her murder from their

windows (Darley & Latané, 1968).

5

inhibition (the presence of others influencing behavior) exists in response to emergencies

(e.g., Latané & Nida, 1981; Latané & Darley, 1970). When a bystander is in the presence

of others, helping behavior decreases. For instance, there was a significant difference

between a bystander’s helping behaviors when they were alone (70%), with a passive

confederate (7%), or with two strangers (20%) in a helping situation regarding a hurt

woman (Latané & Rodin, 1969).

There are at least three reasons why the presence of others can inhibit helping

behavior: audience inhibition, social influence, and diffusion of responsibility (Latané &

Nida, 1981). First, audience inhibition can inhibit helping behavior. The possibility of

misinterpreting a situation in the presence of others could cause a bystander

embarrassment. Thus, the presence of others can inhibit a bystander’s decision to help to

avoid possible negative appraisals from others. Second, social influence can also inhibit

helping behavior. Bystanders use others to help define a helping situation, but this fosters

both correct and incorrect interpretations. For instance, in a helping situation, if a

bystander observes that others are not helping in a given situation, the bystander might

inaccurately interpret the situation as less critical than it really is. Lastly, diffusion of

responsibility can lessen the psychological burden of the cost of not helping in a given

situation. In the presence of others, the responsibilities and costs of helping behavior or

lack thereof can be shared with others (Latané & Darley, 1970; Latané & Nida, 1981).

There are also other determinants that affect both bystanders’ and victims’

decision to call the police. Other determinants that influence the decision to call the

police could include the seriousness of the crime (e.g., injury or financial loss; Skogan,

6

1984), considerations of obligation (e.g., maintain status of being a “good citizen”

Skogan, 1984, p. 121), and culpability (e.g., own past behavior with police; Sparks,

Genn, & Dodd, 1977). There is also evidence that suggests there are racial differences in

the decision to call the police (e.g., Skogan, 1984; Davis et al., 2018).

Racial Differences in Calling the Police

Although there is a lack of psychological literature examining racially based

motivation to call the police, there is research concerning racial differences in reporting

crime to the police. In the 1980s, it was believed there were minimal racial differences in

reporting crime to the police (Skogan, 1984). For instance, in some categories (e.g.,

crimes that involved personal injury), black individuals reported crimes at higher rates

than white individuals (Skogan & Maxfield, 1981). More recently, however, evidence

suggests that white individuals contact police more than black individuals.

Overall, the U.S population consists of over 200 million individuals age 16 and

older, and about 21.1% of these individuals have had contact with the police (about 53.5

million individuals) in the past 12 months. Of this 21.1%, about 11% of individuals

(about 27 million individuals) initiated police contact, and about 7% initiated contact

with police to report a possible crime (about 16 million people; Davis et al., 2018).

Of the 16 million reports to the police regarding a possible crime, about 12

million (75%) were from white individuals, whereas about two million were from black

individuals (11%; Davis et al., 2018). Based on population estimates from the most recent

U.S. Census (2010), relative to the white U.S. population size (73%) in the United States,

white individuals are overreporting to the police for a possible crime, whereas relative to

7

the black U.S. population size (13%) black individuals are under reporting to the police

for a possible crime (U.S. Census Bureau, 2017). The lower rates of reporting by

minority populations could be connected to evidence that suggests that black individuals

are more distrustful of police (Tyler, 2005) and have lower levels of confidence in the

police (Lasley, 1994). Further, there is evidence that suggests that the police have greater

suspicion of minority populations (e.g., Alpert, MacDonald, & Dunham, 2005; Harris,

2002). These factors could influence the racial differences in the decision to contact the

police.

Racial Differences in Arrest Rates

From the 1970s to the 2000s, arrest rates of black individuals have declined

(Travis, Western, & Redburn, 2014); however, changes in society (Blumstein &

Wallman, 2006) and trends in policies (Blumstein & Beck, 1999) can affect arrest rates.

For instance, in the 1980s, there was a large increase in the arrest of black individuals

compared to white individuals, due to black individuals predominately selling the drug,

crack (Blumstein & Wallman, 2006). Further, in the late 1980s, overall drug related arrest

rates were six times higher for black individuals compared to white individuals

(Blumstein & Wallman, 2006). In more recent years, however, drug related arrests of

black individuals were only three to four times higher than for white individuals (Travis

et al., 2014). The decrease of black drug arrests compared to white drug arrests is due to

the emphasis on total drug arrests and greater emphasis on marijuana arrests (Travis et

al., 2014).

8

More generally, white individuals (70%) are arrested at higher rates than black

individuals (27%; FBI Uniform Crime Reporting Program, 2016); however, black arrest

rates are double their actual representation in the U.S. population (Garland, Spohn, &

Wodahl, 2008). Despite experiencing lower arrest rates, black individuals still experience

racial bias. For example, black individuals experience higher rates of traffic stops

compared to white individuals (Harris, 1999; Langton & Durose, 2016; Walker, Spohn,

& DeLone, 2000). Ultimately, these stops result in more searches, tickets, and arrests for

black individuals compared to white individuals (Langton & Durose, 2016; Pierson et al.,

2019). Further, evidence suggests that racial discrimination during the early stages of the

criminal justice process (i.e., arrest, pretrial process, and sentencing) is concerning for

incarceration rates (Weich & Angulo, 2002). If there was no discrimination within the

criminal justice system following initial arrests then black and white individuals would be

imprisoned at the exact same distributions; however, there is evidence of post-arrest

discrimination in incarceration rates (Garland et al., 2008).

Racial Differences in Incarceration Rates

In the United States, there appears to be a disparity of incarceration rates between

black and white individuals (Travis et al., 2014). Historically, U.S. prisons have

contained primarily disadvantaged populations. In the 1970s, about one-third of white

males who dropped out of high school had served time in prison, whereas about two-

thirds of black males who had dropped out of high school had a prison record (Travis et

al., 2014). More recently, from 1995 to 2005, incarceration rates have decreased overall,

9

but there are still more black individuals (40%) in state or federal prisons than white

individuals (35%; Harrison & Beck, 2006).

Further, evidence from 2014 suggests that black individuals are imprisoned at six

times the rate of non-Hispanic white individuals (Travis et al., 2014). As of 2019, black

individuals still comprise about 40% of the U.S. prison systems despite accounting for

only 13% of the U.S population (Sawyer & Wagner, 2019). Ultimately, there is an

overrepresentation of racial and ethnic minorities in prison systems in relation to their

overall population (Nellis, 2016). Collectively this information suggests that race should

be evaluated in understanding calls made to the police as well as arrest and incarceration

rates.

Police officers and the criminal justice system are tools enacting the biases held

by citizens who call the police (Takei, 2018). Although people believe they call police for

justified reasons, this might not be the case. One possible explanation for why people

choose to call the police stems from racial motivation to call police using aversive racism

theory (Gaertner & Dovidio, 1986). Another possibility could be related to individual

variability in risk perception using risk averse motivation (Kahneman & Tversky, 1982).

In the next sections, I will examine these two possibilities.

Aversive Racism Theory

Aversive racism theory (Gaertner & Dovidio, 1986) is consistent with the

American Dilemma (Myrdal, 1944), which suggests that Americans are inconsistent in

their beliefs of equality for all, and their ability to treat black individuals as equal to white

individuals (Dovidio, Mann, & Gaertner, 1989; Loury, 1984). Although America is

10

founded on ideals and values of equality, there seems to be a contradiction of this belief

that is demonstrated by the nation’s history of overt signs of prejudice and discrimination

(Dovidio & Gaertner, 2004; Loury, 1984).

Although prejudice might not be as overt and explicit as it previously has been in

America’s history, prejudice has persisted and become more subtle and unconscious

(Dovidio & Gaertner, 2000). Aversive racism theory (Gaertner & Dovidio, 1986)

explores these changes from overt, explicit forms of prejudice and discrimination to the

increase in unconscious, subtle forms of prejudice and discrimination (Dovidio &

Gaertner, 2000). Even though subtle forms of prejudice might not be as explicitly

detrimental as overt forms of prejudice, they have even stronger and more damaging

repercussions (e.g., “the restriction of economic opportunity;” Gaertner, Dovidio, Nier,

Hodson, & Houlette, 2008, p. 378).

Aversive racism theory (Gaertner & Dovidio, 1986) suggests that aversive racists

generally support equalitarian values; however, aversive racists possess biased feelings,

often unconsciously. Thus, to avoid contradiction, aversive racists are likely to rationalize

their racist attitudes and beliefs to another factor besides race (Dovidio & Gaertner,

2000). For instance, white individuals did not discriminate in their recommendations of

hiring decisions when white or black candidates had clearly strong or weak candidate

qualifications. When qualifications were more ambiguous, however, white individuals

did discriminate in their hiring decisions of black candidates (Dovidio & Gaertner, 2000).

Thus, the ambiguity of the qualifications allowed participants to rationalize their biased

recommendation against a black candidate.

11

Aversive racism creates complex attitudes and feelings in individuals who hold

egalitarian intent but display and implicitly harbor racist feelings (Dovidio & Gaertner,

2000; Gaertner & Dovidio, 2005). Ultimately, this complexity creates an atmosphere of

ambivalence driven by both feelings of equality and implicit negative feelings about

black individuals (Dovidio & Gaertner, 2000; Pearson, Dovidio, & Gaertner, 2009).

Rather than expressing explicit hatred or aggression, aversive racists often feel

uneasiness, physiological arousal, discomfort, or even fear towards black individuals

(Dovidio & Gaertner, 2004; Nail, Harton, & Decker, 2003).

Following the line of aversive racism research, often individuals hold non-

prejudiced attitudes; however, without the decision to call the police clearly defined, the

decision to call the police could be rationalized by other qualities of the situation. For

example, if the situation is late at night, people are yelling, or fists are being pounded on

a table then these factors may be rationalized as the decision to call the police rather than

the race of the perceived suspect. It is possible, however, that race (i.e., black or white)

could be an unconscious factor in the decision to call the police. Thus, individuals may

discriminate in their choice to call the police.

Risk Averse Motivation

Alternatively, motivation to call the police could be related to individual variation

in levels of risk aversion. The concept of risk aversion can be traced back to Daniel

Bernoulli, a Mathematician in 1738 (Kahneman & Tversky, 1982). Based off gambling

research, Bernoulli characterized risk aversion as a characteristic of human preference

(Kahneman & Tversky, 1982; Zhang et al., 2014). Since Bernoulli, risk aversion has been

12

extensively researched in both economic and psychological literature (Zaleskiewicz,

2001). Studies often examine preferential outcomes that motivate either risk averse or

risk seeking behavior. To further understand both of these concepts:

To understand risk aversion, imagine that you are given a choice between two

options. The first is a sure gain of $80. The second is a risky prospect that offers

an 85 percent chance of winning $100 and a 15 percent chance of winning

nothing. Most people who are presented with this choice prefer the certain gain to

the gamble, in spite of the fact that the gamble has a higher "monetary

expectation" than the certain outcome…A choice is risk averse if a certain

outcome is preferred to a gamble with an equal or greater monetary expectation.

A choice is risk seeking, on the other hand, if a certain outcome is rejected in

favor of a gamble with an equal or lower monetary expectation. (Kahneman &

Tversky, 1982, p. 160)

More simply put, a risk averse decision is the tendency to prefer the certain option

compared to the uncertain option (Paulsen et al., 2012); risk seeking behavior is the

tendency to prefer the uncertain option (Kahneman & Tversky, 1982).

There are three individual characteristics that have been identified as likely

determinants of risk behavior (i.e., risk averse or risk seeking behavior): (1) risk

preferences, (2) risk perceptions, and (3) risk propensity. The first determinant, risk

preferences, refers to an individual’s overall attitude toward risk (Wen, He, & Chen,

2014). Some individuals enjoy the thrill and challenge that risk can entail and others do

13

not (Sitkin & Pablo, 1992). For example, consistently across several countries, investors’

risk preferences are risk seeking (Wen et al., 2014).

The second determinant, risk perception, is created through an individual

assessment of a situation, estimates of the extent and controllability of risks, and the

confidence in those estimates (Sitkin & Pablo, 1992). Risk perception is a personal

process and decision about health and safety (Ropeik, 2012), which incorporates thoughts

of “the probability of something bad happening” (Brown, 2014, p. A277). After an initial

assessment of a situation, individuals can assess the amount of risk present and decide to

take action based on their own level of discretion of perceived risk (Sitkin & Pablo,

1992). Often, perceived risk can result in heightened senses (i.e., sights, sounds, smells)

and can affect memories, which can then exacerbate perceived risk and fear (Brown,

2014). For instance, hearing a higher probability of the chance of a car crash fatality

increases risk perception and risk averse behavior (i.e., frequent seat belt use).

The third determinant, risk propensity, is characterized as risk taking tendencies.

Based on the risk taking tendencies of an individual, risks are evaluated in terms of taking

or avoiding risks (Sitkin & Pablo, 1992). For instance, researchers found that business

executives who were more mature (i.e., older, seniority) were consistently more risk

averse compared to individuals who were less mature (i.e., younger; MacCrimmon &

Wehrung, 1990).

Multiple factors can influence individual variability in the perception of risk and

ultimately, risk behavior, aside from the three individual characteristics: risk preferences,

risk perception, and risk propensity. Another factor that could influence risk behavior is

14

group contexts (Janis, 1972). While in a group, individuals can become victims to the

phenomenon, groupthink (Janis, 1982). Groupthink suggests that group cohesion

becomes so strong that thoughts and values become likeminded and personal doubts are

dismissed within the group (Janis, 1982). For example, there were signs and antecedents

of groupthink surrounding the decision to launch the space shuttle Challenger that

exploded seconds after its launch (Esser & Lindoerfer, 1989). Further, emotions can also

influence risk behavior (Kusev et al., 2017). For instance, some research suggests that

anxious and depressive states are connected to risk averse preferences (Miu, Heilman, &

Houser, 2008; Yuen & Lee, 2003). Hormones, such as cortisol or testosterone can also

influence risk behavior (Kusev et al., 2017). Individuals with higher levels of testosterone

tend to take greater risks (Stanton, Liening, & Schultheiss, 2011) whereas individuals

who experience chronically raised levels of cortisol tend to be more risk averse (Kusev et

al., 2017).

Collectively, the preference for risk aversion can depend on a number of factors.

Risk averse motivation could stem from influences of individual characteristics (e.g., risk

preference, risk perception, and risk propensity). Thus, some individuals are more risk

averse, and may be more willing to call the police in a possible risk situation. Further,

risk perceptions could be influenced by evidence that suggests white individuals (and

black individuals) hold negative stereotypes about the black community (Plous &

Williams, 1995), and that individuals link black men with criminality (Kleider-Offutt,

Bond, & Hegerty, 2017). These negative stereotypes can influence the perception of risk

15

in a given situation. If a risk averse individual holds a negative stereotype of a black

individual, then this could perpetuate the need to call the police in a crime context.

Other Explanations: Gender and Political Orientation

Demographic factors may also influence the decision to call the police. According

to the most recent Police-Public Contact Survey, women initiate contact with police and

report possible crime more often than men (Davis et al., 2018). Further, women express

more confidence in the police than men. Women often also hold more favorable

sentiments towards police than men because their relationship with police is often less

antagonistic, and women are more likely to make service requests to police compared to

men (Cao, Frank, & Cullen, 1996). Therefore, women may be more likely to call the

police more than men.

Historically, America has been politically divided in its support for the police

(Ekins, 2016). For instance, political conservatives tend to hold more positive attitudes

towards police than political liberals (e.g., Hindelang, 1974; Huang & Vaughn, 1996;

Zamble & Annesley, 1987). More recently, only 33% of liberals rated the police as “very

warm,” whereas 74% of conservatives rated the police as “very warm” (Fingerhut, 2017).

These differences could stem from the differentiation in values supported by liberals and

conservatives; specifically, conservatives place greater emphasis on authority, which is

represented by the police (Graham, Haidt, & Nosek, 2009). Thus, political orientation

may affect the decision to call the police.

16

CHAPTER 2.

CURRENT STUDY

There seems to be a surplus of examples of racially biased calls made to the

police (Takei, 2018). These biased calls share two common themes: (1) individuals seem

to be behaving in seemingly harmless activities (e.g., napping in a dorm common area;

Griggs, 2018), and (2) the perceived suspect is black. The current study aimed to further

understand the motivation to call the police through the lens of aversive racism theory

(Gaertner & Dovidio, 1986) and risk averse motivation (Kahneman & Tversky, 1982).

Aversive racism theory (Gaertner & Dovidio, 1986) suggests that aversive racists

discriminate when bias can be rationalized to another factor besides race. Aversive racists

generally endorse egalitarian values, which makes understanding and recognizing

aversive racism difficult (Dovidio & Gaertner, 2000). The aversive racism theory

framework could be applied to understand the motivation to call the police. For instance,

regarding the call made to police on the canvassing state representative, the caller

indicated they placed the call because of the suspicious behavior of the politician. Thus,

the caller rationalized the odd behavior of the black state representative— using her cell

phone after visiting each house— as justification to call the police (Archie & Smith,

2018).

Individuals may also be influenced by risk averse motivation. Risk averse

motivation (Kahneman & Tversky, 1982) is the tendency to prefer the certain option

compared to the uncertain option (Paulsen et al., 2012). Risk aversion can be influenced

by various determinants of an individual’s character (i.e., risk perception; Sitkin & Pablo,

17

1992). Examining risk averse motivation could be used to understand the motivation to

call the police. For instance, regardless of race, for a risk averse individual, a call to the

police in a risky situation would lead to a certain outcome of the police coming, which

could provide a sense of relief and safety.

Further, both race of a perceived suspect and risk aversion may influence the

decision to call the police. Evidence suggests that Americans still hold stereotypical,

negative views of black individuals, such as linking them to crime (Kleider-Offutt et al.,

2017). Thus, an assessment of a black individual in a possible crime situation could

influence a risk averse individual to call the police to provide a sense of certainty in a

perceived risky situation.

Additionally, demographic factors may influence the decision to call the police.

Women often have more favorable views of police (Cao et al., 1996) and initiate contact

with police more than men (Davis et al., 2018). Further, conservatives compared to

liberals also have more favorable views of the police (Hindelang, 1974; Huang &

Vaughn, 1996; Zamble & Annesley, 1987) and more confidence in the police (Stack &

Cao, 1998). Thus, women and conservatives may be more likely to call the police than

men and liberals.

The current study used an exploratory approach to examine the motivation to call

police through both aversive racism theory and risk averse motivation. To test these two

frameworks, participants were recruited from Amazon Mechanical Turk (mTurk) and

were asked to provide their evaluations and attitudes about a mock crime summary.

Participants were randomly assigned to one of two conditions that contained either a

18

black or white perceived suspect (i.e., the customer in the scenario). In each condition,

participants read a scenario about an altercation (i.e., yelling and fists pounding on the

counter) between a store clerk and a store customer at a convenience store. After reading

the scenario, participants were asked to provide their attitudes and perceptions of both the

scenario (e.g., “To what extent, if any, do you think the scenario was risky?”) and the

perceived suspect (e.g., “To what extent, if any, was the customer at the front of the store

dangerous?”), and then participants completed the manipulation check. Some of these

items were used as the dependent variables within analyses. Then participants completed

a risk perception scale (e.g., How risky is “Walking home alone at night in an unsafe area

of town.”). This scale was used to assess whether participants were risk averse or risk

seeking. After the risk perception scale, participants completed demographic measures.

Two of the demographic questions relating to gender and political orientation (assessed

three domains) were used in analyses: “What is your gender identity?” and “How would

you describe your views on current social issues, economic issues, and foreign policy?”

Lastly, participants completed an honesty check and open-ended items regarding the

intent of the study, possible reasons to exclude data, and a comment section for any

possible comments the participant had for the researcher.

Research Questions

Research questions were used rather than hypotheses based on the lack of

research in this area to form hypotheses. Consistently throughout the study, race of the

perceived suspect was operationalized as the race of the customer in the scenario (i.e.,

black or white); risk perception was operationalized as a score on the 30-Item Doman-

19

Specific Risk-Taking Scale (DOSPERT scale; Blais & Weber, 2006a); the decision to

call the police was operationalized as self-reports of both the likelihood, dichotomous

choice of the decision to call the police, and the agreement with someone else’s decision

to call the police. For my exploratory analyses, gender was operationalized with the

single item, “What is your gender identity?” and political orientation was operationalized

as a mean value of an overall score assessing three domain areas: “social issues,”

“economic issues,” and “foreign policy” (adapted from Inbar & Lammers, 2012)

1. Are participants more likely to call the police when the perceived suspect is black

compared to white? According to aversive racism theory (Gaertner & Dovidio,

1986) when bias can be rationalized to another factor besides race, then

discrimination can happen. When the perceived suspect in the scenario is black,

the scenario (e.g., yelling, fists pounding on the counter) may cause individuals to

rationalize that the decision to call the police is important and necessary.

2. Are participants who are more risk averse more likely to call the police? Based on

previous research suggesting that risk averse individuals prefer the certain option

compared to the uncertain option (Kahneman & Tversky, 1982; Paulsen et al.,

2012) then risk averse individuals would prefer the certain outcome of police help

in the choice to call the police.

3. Are participants who are risk averse more likely to call the police when the

perceived suspect is black compared to white? Evidence suggests that risk averse

individuals have various characteristics (e.g., risk perception) that are influential

in their risk behavior (Sitkin & Pablo, 1992). Further, the race of the perceived

20

suspect could be influential in the assessment of perceived risk. For instance,

when the perceived suspect in the scenario is black, the assessment of risk

perception might influence the decision to call the police due to stereotypes that

black individuals are linked to criminality (Kleider-Offutt et al., 2017). Thus,

calling the police will provide both certainty and security in an uncertain situation

for risk averse individuals.

Exploratory Questions

4. Does risk perception mediate the relationship between race of the perceived

suspect and choice to call the police? The individual assessment of risk perception

could exacerbate the influence of the race of the perceived suspect on the decision

to call the police.

5. Are there gender differences in the choice to call the police? There is evidence

that suggests women have more favorable views and higher confidence in the

police than men (Cao et al., 1996). Thus, women might be more likely to call the

police than men.

a. Is there an interaction between gender and risk perception in the choice to

call the police? Evidence suggests that women are more risk averse than

men in many areas of life (e.g., Jianakoplos & Bernasek, 1998; Spigner,

Hawkins, & Loren, 1993); thus, women who are risk averse might be

especially likely to report that they would call the police.

6. Are there political orientation differences in the choice to call the police?

Evidence suggests that conservatives have more positive feelings toward the

21

police and additionally, have a value system that better aligns with police offers

roles (i.e., authority figures) compared to liberals (Hindelang, 1974; Huang &

Vaughn, 1996; Zamble & Annesley, 1987; Graham et al., 2009). Thus,

conservatives might be more likely to call the police than liberals.

a. Is there an interaction between political orientation and risk perception in

the choice to call the police? Existential motives of threat and fear are

most often linked to political conservatism (Jost, Glaser, Kruglanski, &

Sulloway, 2003); thus, political conservatives who are risk averse might

be especially likely to report that they would call the police.

22

CHAPTER 3.

METHOD

Pretest

I initially generated four scenarios to test for use in the study. In all the scenarios,

the reader imagined they left work and stopped to get gas at a convenience store when

they witnessed an altercation between the convenience store clerk and another

convenience store customer (who was either black or white). Details, however, were

changed for each scenario based on the concept of perceived risk; thus, the scenarios

were created to represent a possible range of perceived risk. Specifically, the details

surrounding the altercation between the store clerk and the other convenience store

customer were altered in each scenario. In one scenario aspects of a robbery unfold (i.e.,

yelling, demanding of money) and a gunshot occurs, in another scenario only the aspects

of the robbery unfold (i.e., yelling, demanding of money), whereas in another scenario

the altercation involves only incoherent yelling and the customer pounding his fists on

the counter. In the last scenario, the reader takes notice of a conversation between a store

clerk and convenience store customer.

To determine which scenario represented an account of ambiguous risk, 56

undergraduate students at a Midwestern University rated each of the four scenarios using

the two items: “To what extent, if any, do you believe this situation is risky?” using a 10-

point Likert scale from, 1 (Not at all Risky) to 10 (Extremely Risky) and “To what extent,

if any, do you believe you need to call the police?” using a 10-point Likert scale from, 1

(Strongly Disagree) to 10 (Strongly agree). Ambiguity was determined by a mean value

23

of the two items (i.e., risk question and need for police question) ranging around 5.0-7.0.

These qualifications were similar to Dovidio and Gaertner’s (2000) criteria for

determining ambiguous qualifications for potential job candidates. Furthermore, an

ambiguous scenario made the appropriate decision to call or not call the police more

difficult, which aids in the exploration of discrimination. The scenario deemed

ambiguous and used in the current study (Appendix A) involved aspects of yelling

between the store clerk and customer and the customer’s fists pounding on the counter.

Participants

I conducted a power analysis to determine the number of participants needed for

this study. Due to the lack of psychological literature on the current topic, a similar topic

using aversive racism theory was used for the power analysis. The effect sizes (Pearson’s

r) for this study were based on correlations of a racial stereotyping item and two

measures of the approval for use of police force (i.e., regarding excessive police force

and reasonable police force; r = .12) and a racial stereotyping scale and antipathy scale (r

= .35; Barkan & Cohn, 1998). These two correlations were averaged to reach a small

effect size. To obtain .90 power with a two-tailed test, and small effect size of .20, I

needed a total of 259 participants using Cohen’s tables (Cohen, 1988). However, due to

possible data sample issues with mTurk data (e.g., attrition, inattention; Buhrmester,

Talaifar, & Gosling, 2018), I decided to oversample by 20 percent to account for

participants that would later need to be excluded. With a 20 percent increase, I needed a

sample size of 311 participants to examine my research questions. Increasing the sample

size by 20% assured that my original target sample size of 259 would be met. Participants

24

were all recruited from an online data collection platform, Amazon Mechanical Turk

(mTurk users).

Participants were recruited using the TurkPrime website and were compensated

$1.00 for their participation. Participants had to have a HIT approval rating of 95% or

better and have completed between 5,000 and 50,000 HITS approved to participate.

There were initially 332 participants recruited from mTurk, and after the deletions based

on the exclusion criteria there were 295 mTurk participants.

Table 1

Demographic Characteristics

Demographics Mechanical Turk

participants

Gender Identity Male 56%

Age Age 38.87 (11.59)

Race/Ethnicity White or Caucasian 74%

Black or African American 11%

Asian or Asian American 8%

Hispanic or Latinx 7%

Multiracial 1%

Education Bachelor’s degree 43%

Associate degree 21%

High School diploma or less 21%

Graduate degree 11%

(table continues)

25

Political Party

Identification

Democrat 46%

Independent 27%

Republican 21%

No affiliation 5%

Other affiliation (e.g., Libertarian) 1%

Political Orientation Very Liberal 18%

Liberal 33%

Moderate 28%

Conservative 17%

Very Conservative 4%

Note. n = 290-295. The percentages provided are based on data of participants who

met all inclusion criteria. Parenthesis indicate standard deviation.

Procedure

Participants read an electronic version of the informed consent before proceeding

to the study (Appendix B). Participants were randomly assigned to read an ambiguous

risk scenario that contained either a black or a white customer (i.e., perceived suspect),

and were required to stay on this page for 30 seconds to ensure they read the scenario.

The scenario placed the reader at a convenience store at night when an altercation occurs

between a store clerk and a store customer (i.e., perceived suspect). The altercation

involved yelling and the customer pounding his fists on the counter of the convenience

store. During the altercation between the store clerk and customer, the reader learns the

race of the customer as either a young black or white male. Following the scenario,

participants completed questions regarding their likelihood to call the police (i.e., Likert

26

scale), their choice to call the police (i.e., yes or no), and their agreement with someone

else’s decision to call the police (i.e., yes or no); perceptions of the scenario, police

involvement, and the customer in the scenario (i.e., perceived suspect); and the

manipulation check in a randomized order.

Then participants completed a risk perception scale and demographic measures.

Lastly, participants completed an honesty check and open-ended response items that

asked about the purpose of the study, reasons to exclude data, and participant comments

for the researcher. Before concluding the study, participants read the debriefing form

(Appendix C).

Variables and Measures

Evaluation Questions

The evaluation questions (author-generated; Appendix D) assessed the

perceptions and attitudes associated with the scenario and customer through seven items.

All seven items were answered by participants in randomized order. Three of the items

were used to examine the evaluations of the police, (i.e., “To what extent, if any, do you

worry that calling the police would bring you trouble?”), the customer in the scenario,

(i.e., “To what extent, if any, was the customer in the front of the store dangerous?”) and

the scenario overall, (i.e., “To what extent, if any, do you think the scenario is risky?”)

using a 10-point Likert scale from 1 (Strongly disagree) to 10 (Strongly Agree). Four

items of the evaluation questions were used as the dependent variables:

“Based on this scenario, what is the likelihood that you would call the

police?” (Likelihood question)

27

“If someone else saw the same scenario as you and they decided to call

the police, what is the likelihood that calling the police is the correct

decision?” (Likelihood question)

“Based on the scenario you previously read, would you call the police?”

(Dichotomous choice question)

“If someone else saw the same scenario as you and they decided to call

the police, do you agree or disagree with that choice?” (Dichotomous

choice question)

These items were assessed with either a 10-point Likert scale, 1 (Not at all likely)

to 10 (Extremely likely) or a dichotomous choice, “Yes” or “No.” Both likelihood

questions were combined to create an overall likelihood score, whereas the dichotomous

choice questions were examined separately within analyses. The two likelihood questions

had a reliability of ⍺ = .84, whereas the dichotomous choice questions had a reliability of

⍺ = .68.

Manipulation Check

The manipulation check included a single multiple-choice question asking the

race of the customer at the front of the store in the scenario (Appendix E).

30-Item Domain-Specific Risk-Taking Scale (DOSPERT)

The 30-item DOSPERT (Blais & Weber, 2006a; Appendix F) contains five

subscales (i.e., ethical, financial, health/safety, recreational, and social) that assess risk

perception. Using a gut level assessment, participants were asked to evaluate how risky

the action or behavior was in each item using a 7-point Likert rating scale, ranging from 1

28

(Not at all risky) to 7 (Extremely risky). Example items include: “Disagreeing with an

authority figure on a major issue” (social); “Bungee jumping off a tall bridge”

(recreational); “Drinking heavily at a social function” (health/safety); “Not returning a

wallet you found that contains $200” (ethical); "Investing 10% of your annual income in

a new business venture” (financial). Blais and Weber (2006a, 2006b) found good

construct validity and reliability of the subscales ranging from .74 to .83 (mean ⍺ = .79).

Subscale reliability in this study ranged from ⍺ = .78 to .83 (mean ⍺ = .81). In the

current study, I used the entire 30-item scale in my analyses, and the overall reliability

was ⍺ = .92. The overall 30-item DOSPERT scale score can be used as a comprehensive

form of assessment (Blais & Weber, 2006b).

Demographic Questions

The demographics questions (Appendix G) collected basic demographic

information (e.g., gender, race/ethnicity, political orientation) about each participant. For

example, “What is your race/ethnicity? Check all that apply.” The demographic items

regarding gender and political orientation were used in analyses. Gender was collected

through obtaining gender identity: “What is your gender identity?” and political

orientation was obtained from assessing three domains areas: “social issues,” economic

issues, and “foreign policy” from 1 (Very conservative) to 5 (Very liberal; adapted from

Inbar & Lammers, 2012).

Additional End-of-Study Questions

The additional end-of-study questions examined participant honesty (i.e., “How

honest were your answers throughout the study? You will receive payment regardless of

29

what you answer.”) and open-ended questions that requested participant input regarding

the study (e.g., “What do you think the current study was about?”; Appendix H).

30

CHAPTER 4.

RESULTS

Exclusion Criteria

Features were enabled within TurkPrime that aided in the exclusion process.

TurkPrime blocked mTurkers on the universal exclude workers list and blocked

suspicious geo-locations.

Data were excluded from analyses if the study was discontinued prematurely (less

than 25% of the study completed), if participants were not U.S. citizens, if the total time

to complete the study was below 90 seconds, if participants inaccurately answered the

manipulation check, if participants reported they were “not at all honest” or only “slightly

honest” during the study, and if participants failed the attention check. As an attention

check, participants reported both their age and year born. Data were removed from

further analyses if these two items (i.e., age and year born) were not within two years of

each other. Additionally, data were excluded from analyses if participants objected to

their data being used in analyses. If there were duplicate IP addresses, then the data from

the second sample was removed. Using Mahalanobis distance, univariate outliers

exceeding a z-score of ± 3.29 were removed, as defined by Mertler and Vannatta (2013).

Data from multivariate outliers were determined and removed if the Mahalanobis

distance values exceed the chi-square value of 20.515 (Table 2).

31

Table 2

N of Cases of Data Removed from Analyses

Exclusion Criteria Mechanical

Turk

participants

Discontinuing the study 15

Not a U.S. citizen 4

Timing 0

Manipulation check 11

Honesty check 4

Attention check 1

Objection to use of data 0

Duplicate IP address 0

Univariate outliers 0

Multivariate outliers 2

Total Remaining N 295

Assumptions

Before conducting analyses, frequencies, distributions, and ranges were evaluated

for each measure and variable. Violations of normality were assessed through substantial

skewness and kurtosis values. For all measures and variables, skewness and kurtosis were

near -1 and +1 (Mertler & Vannatta, 2013); thus, no variables required transformation

(Kline, 1998). Normality was confirmed by the Kolmogorov-Smirnov test statistic.

Missing values were identified and only viably treated for the 30-Item DOSPERT scale.

The eight missing data values for the 30-Item DOSPERT scale were handled the same as

32

Blais and Weber’s (2006a) standards. Therefore, sample mean values replaced the eight

missing data points based on the criteria that none of the missing values came from the

same participant. Homogeneity of variances was confirmed with Levene’s Test, and

homoscedasticity was confirmed from bivariate scatterplots and statistically using Box’s

M. Scatterplot matrixes indicated there was acceptable linearity based on the appearance

of elliptical shapes (Mertler & Vannatta, 2013).

Plan for Analysis

Before conducting analyses, I examined the relationships between the dependent

variables using bivariate correlations and frequencies. These analyses indicated which of

the items could be combined for analyses and which of the items could not be combined

for analyses. Then, in relation to the dependent variables, I examined three scenario

evaluation items (i.e., evaluations of the scenario, involvement of the police, and the

perceived dangerousness of the customer) using bivariate correlations and independent

samples t-tests. These items were examined to provide a preliminary understanding of the

dependent variables. Further, I examined the correlations among the variables by

condition (i.e., black or white perceived suspect). This provided information regarding

the relationships among my variables.

To examine my research questions, the predictors of risk perception and political

orientation were mean centered. The mean of each variable was subtracted from each

variable value and the predictors of gender and race of the customer were dummy coded

(Irwin & McClelland, 2001). First, I conducted one hierarchical linear regression using

the total likelihood to call police score as the dependent variable. The predictor variables

33

of age and gender were entered in the model first as control variables. The demographic

factors of age and gender were added to the model because evidence suggests they could

be influential in regards to the decision to call the police. Older individuals often have

increased contact with the police (Sever & Youdin, 2006), and women have more

positive (Cao et al., 1996) and frequent contact with police than men (Davis et al., 2018).

The variable gender was dummy coded (i.e., men = 1 and women = 0), and data from

participants who did not identity in these two categories were removed. Then, risk

perception and race of the customer in the scenario were added to the model. Race of the

customer was dummy coded (i.e., black = 1 and white = 0). Next, the interaction of risk

perception and race of the customer in the scenario was added to the regression model.

The interaction term was calculated by multiplying the risk perception scale and the race

of the customer in the scenario (Iacobucci, Schneider, Popovich, & Bakamitsos, 2016).

Next, to examine my exploratory questions and to avoid repercussions to power, I

ran a second linear regression including the addition of the interaction term of risk

perception and gender. The interaction term was calculated by multiplying the risk

perception scale and gender (Iacobucci et al., 2016). Only two blocks were examined for

this model. Age, gender, race of customer, and risk perception are in the first block, and

the second block contained the two interaction variables.

Then, to examine my next exploratory questions and to avoid repercussions to

power, I ran a third linear regression including the variable political orientation and the

interaction term of risk perception and political orientation. The interaction term was

calculated by multiplying the risk perception score and political orienatation (Iacobucci et

34

al., 2016). Only two blocks were examined for this model. Age, gender, race of customer,

risk perception, and political orientation are in the first block, and the second block

contained the three interaction variables.

I also conducted two hierarchical logistic regressions to assess my research

questions, using the two dichotomous choice dependent variables: the dichotomous

choice to call police item and the dichotomous choice agreement with someone else’s

decision to call the police item. These analyses are presented in sequential order to

prevent redundancy since the analyses were identical besides the dependent variable. For

these models, the variables were handled the same as in the linear regression analyses

(i.e., mean centering, dummy coded, calculation of interaction terms), but there were

different dependent variables. First, for the logistic regression model, age and gender

were added in the model first. Then risk perception and race of the customer in the

scenario were added to the models. Third, the interaction term of risk perception and the

race of the customer in the scenario were added to the models.

Next, to examine my exploratory questions and to avoid repercussions to power, I

ran a two more logistic regressions, which included the addition of the interaction term of

risk perception and gender. Only two blocks were examined for this model. Age, gender,

race of customer, and risk perception are in the first block, and the second block

contained the two interaction variables.

Lastly, to examine my next exploratory questions and to avoid repercussions to

power, I ran two more logistic regressions, including the variable political orientation and

the interaction term of risk perception and political orientation. Only two blocks were

35

examined for this model. Age, gender, race of customer, risk perception, and political

orientation are in the first block, and the second block will contain the three interaction

variables. Overall, nine regressions were conducted to aid in the examination of the

research questions. Separating the analyses assisted in interpretation and dissemination of

the results regarding the research questions.

Additionally, I conducted one exploratory mediational analysis to determine

whether risk perception mediated the relationship between the race of the customer and

the choice call to the police (i.e., single-item dichotomous choice question). For the

mediational analysis, I completed three separate regression analyses (i.e., two linear and

one multiple regression), and then completed a Sobel test (Preacher & Leonardelli, 2001)

to examine the indirect effect of path a and path b (Baron & Kenny, 1986).

Dependent Variables Examination

The four items: (1) “Based on this scenario, what is the likelihood that you would

call the police?”; (2) “If someone else saw the same scenario as you and they decided to

call the police, what is the likelihood that calling the police is the correct decision?”; (3)

“Based on the scenario you previously read, would you call the police?”; (4) “If someone

else saw the same scenario as you and they decided to call the police, do you agree or

disagree with that choice?” were used as the dependent variables in analyses. Initially, the

first two items examining (1) the likelihood to call police and (2) the likelihood to have

someone else call police were going to be combined together, and the latter two items, (3)

the dichotomous choice to call the police and (4) the dichotomous choice agreement with

someone else’s decision to call police item were also going to be combined together.

36

After a preliminary examination of the data, however, results revealed that only the two

likelihood items should be combined; thus, the two dichotomous choice questions were

assessed independently in analyses.

The two likelihood items were combined to create a total likelihood score. There

was a strong significant correlation between the two likelihood items: (1) the likelihood

to call police (M = 4.89; SD = 2.94) and (2) the likelihood to agree with someone else’s

decision to call the police (M = 6.06; SD = 2.69), r = .72, p < .001, n = 294. Previous

research has combined scales with a correlation of r = .70 (e.g., Stillman, Medvedev, &

Ferguson, 2017); thus, it was deemed appropriate to combine the two questions. The total

likelihood score was used as a dependent variable to assess the research questions.

The two dichotomous choice items were not combined to create an overall

dichotomous choice score. Although there was strong significant correlation between the

two dichotomous choice items: (3) the dichotomous choice to call police and (4) the

dichotomous choice agreement with someone else’s decision to call the police item,

r(292) = .50, p < .001 (Table 3) these items were not combined in analyses. Despite the

significant correlation of the two items, about 41% of participants changed their decision

between the choice to call the police and the agreement with someone else’s decision to

call the police (Table 4). Only 38% of participants said they would call the police

whereas 63% agreed with someone else’s decision to call the police. This change in

perception of the choice to call the police and the agreement with someone else’s

decision to call police could be possibly explained by previous literature examining

bystander influence (e.g., Latané, 1981; Latané & Darley, 1970; Latané & Nida, 1981) or

37

incorrect interpretations of the items due to the wording of the two items. Based on these

results, both dichotomous choice questions “Based on the scenario you previously read,

would you call the police?” and “If someone else saw the same scenario as you and they

decided to call the police, do you agree or disagree with that choice?” were assessed as

separate dependent variables to assess the research questions.

Table 3

Correlations of the Dependent Variables

Variables 1 2 3 M(SD)

1. Likelihood:

Call Police

4.89(2.94)

2. Likelihood:

Someone Else

.72** 6.06(2.69)

3. Dichotomous:

Call Police

.82*** .61*** NA

4. Dichotomous:

Someone Else

.49*** .58*** .52*** NA

Note. (ns = 294-295); ***: p < .001; **: p < .01; *: p < .05.

1. The likelihood to call the police item.

2. The likelihood to agree with someone else’s decision to call the police item.

3. The dichotomous choice item to call the police item.

4. The dichotomous choice agreement with someone else’s decision to call the police.

Table 4

Dichotomous Choice Item Response

Call Police (%) Someone Else Call Police (%)

111 (38%) 187 (63%)

183 (62%) 108 (37%)

Note. (ns = 294-295).

Evaluations of the Scenario, Police Involvement, and the Suspect

Before the research questions were explored, analyses were also conducted to

understand the evaluations of the scenario, police involvement, and the suspect in relation

to the dependent variables, using these three items:

38

“To what extent, if any, do you think the scenario is risky?”

“To what extent, if any, do you worry that calling the police would bring

you trouble?”

“To what extent, if any, was the customer in the front of the store

dangerous?”

There was a significant positive association between the perceived risk in the

scenario and the dichotomous choice to call the police item, r = .50, p < .001 n = 294.

There was also a significant positive correlation between the perceived risk of the

scenario and the dichotomous choice agreement with someone else’s decision to call the

police, r = .45, p < .001 n = 295. Lastly, there was a significant positive correlation

between the perceived risk of the scenario and the total likelihood to call the police score,

r = .68, p < .001, n = 294 (Table 5).

Based on these correlations, independent samples t-test were conducted using the

dichotomous choice dependent variables and the perceived risk of scenario item. First,

there was a significant difference between the decision to call the police, (M = 7.37; SD =

1.38) and to not call the police, (M = 5.26; SD = 1.97), t(292) = 9.882, p < .001, d = 1.24.

Participants rated the scenario as riskier when they decided to call the police compared to

when they did not call police. The scenario was also perceived as more risky when there

was agreement with someone else’s decision to call the police, (M = 6.75; SD = 1.73)

than disagreement with someone else’s decision to call the police, (M = 4.83; SD = 1.98),

t(293) = 8.626, p < .001, d = 1.03.

39

Considering the item, police involvement potentially bringing trouble, there was a

nonsignificant association between police involvement bringing trouble and the

dichotomous choice to call the police item, r = -.01, p = .09, n = 294. There was also a

nonsignificant association between police involvement bringing trouble and the

dichotomous choice agreement with someone else’s decision to call the police, r = -.05, p

= .41 n = 295. Lastly, there was a nonsignificant association between police involvement

bringing trouble and the total likelihood to call the police score, r = -.06, p = .30, n = 294

(Table 5). Due to the nonsignificant correlations, independent samples t-tests were not

conducted.

Concerning the item, how dangerous was the customer in the scenario, there was

a significant positive association between the perceived danger level of the customer and

the dichotomous choice to call the police item, r = .61, p < .001 n = 294. There was also

a significant positive correlation between the perceived dangerousness of the customer

and the dichotomous choice agreement with someone else’s decision to call the police, r

= .51, p < .001 n = 295. Lastly, there was a significant positive correlation between the

perceived dangerousness of the customer and the total likelihood to call the police score,

r = .747, p < .001, n = 294 (Table 5).

Based on these correlations, independent samples t-test were conducted using the

dichotomous choice dependent variables and the perceived dangerousness of the

customer item. First, there was a significant difference between the decision to call the

police, (M = 7.55; SD = 1.65) and to not call the police, (M = 4.76; SD = 1.86), t(292) = -

12.988, p < .001, d = 1.59. Participants rated the participant as more dangerous when they

40

decided to call the police compared to when they did not call the police. The customer

was also rated as more dangerous when there was agreement with someone else’s

decision to call the police, (M = 6.67; SD = 1.97) than disagreement with someone else’s

decision to call the police, (M = 4.31; SD = 1.87), t(293) = -10.084, p < .001, d = 1.23.

Collectively, these results indicate that when the scenario was perceived as riskier

there was greater reported likelihood to call the police and more agreement with someone

else’s decision to call the police. Additionally, when the customer in the scenario was

perceived as more dangerous there was greater reported likelihood to call the police and

more agreement with someone else’s decision to call the police. Thus, the assessment of

possible risk and danger were important aspects in the decision to call the police and the

agreement with someone else’s decision to call the police.

In addition to examining the evaluation questions and the dependent variables, I

examined the correlations among the variables by condition (i.e., black and white

perceived suspect). The correlations were fairly consistent in each condition (Table 6).

For instance, there are strong significant correlations among the dependent variables in

both conditions. Further, the age variable does not significantly correlate among the

dependent variables in either conditions. An interesting pattern emerges, however,

between the risk perception score and the three dependent variables. In the black

condition, the risk perception score significantly correlates with the three dependent

variables; however, in the white condition, the risk perception score only significantly

correlates with the dichotomous choice agreement with someone else’s decision to call

the police. This same pattern emerges for political orientation. In the black condition, all

41

three of the dependent variables are significantly correlated with political orientation,

whereas in the white condition, none of the dependent variables are significantly

correlated with political orientation.

Table 5

Correlations of the Evaluation Questions and the Dependent Variables

1 2 3 4 5

1. Risky

2. Trouble .03

3. Dangerous .76*** .04

4. Call Police .50*** -.01 .61***

5. Someone

Else Call Police

.45*** -.05 .51*** .52***

6. Likelihood

Score

.68*** -.60 .75*** .75*** .57***

Note. (ns = 293-295); ***: p < .001; **: p < .01; *: p < .05.

1. Risky: a higher value indicates more perceived risk.

2. Trouble: a higher value indicates more perceived trouble.

3. Dangerous: a higher value indicates more perceived danger.

4. The dichotomous choice to call police: single item.

5. The dichotomous choice agreement with someone else’s decision to call the police:

single item.

6. Total likelihood to call police score: composite score.

42

Table 6

Correlations of the Variables by Condition

1 2 3 4 5 6 7

1.Call Police .52** .77** -.12 -.06 .24** -.18*

2. Someone

Else Call

Police

.52** .60** -.10 -.06 .26** -.18*

3. Likelihood

Score

.77** .55** -.10 -.12 .29** -.26**

4. Age .04 -.03 .06 -.20* .13 -.14

5. Gender -.25 -.18* -.27** -.21** -.31** -.02

6. Risk .12 .16 .25** .17* -.31** -.10

7. PO .04 -.06 -.09 -.09 -.04 -.02

Note. Correlations above the diagonal represents the black perceived suspect condition

and the correlations below the diagonal represents the white perceived suspect condition.

ns = 140-149; **: p < .01; *: p < .05. 1. The dichotomous choice to call police item. 2.

The dichotomous choice agreement with someone else’s decision to call the police item.

3. Total likelihood to call police score. 4. Age of the participant. 5. Gender of the

participant (- female and + male). 6. Risk perception score. 7. Political orientation score

(a higher score indicates liberal ideology and a lower score indicates conservative

ideology).

Hierarchical Linear Regression: Likelihood to Call Police

First, the control variables, age and gender, were added to the model, [R2 = .040,

R2adj = .033, F(2, 285) = 5.951, p < .01]. Next, the addition of race of the customer in the

scenario and risk perception to the model added significantly, [R2 = .086, R2adj = .073,

F(4, 283) = 7.099, p < .001]. The interaction term between risk perception and race of the

customer, however, did not significantly add to the regression model, [R2 = .086, R2adj =

.070, F(5, 282) = .001, p = .97].

43

Research Question 1

First, I examined whether participants were more likely to call the police when the

customer was black compared to white with a hierarchical linear regression. As shown in

Table 7, Block 2, there was not a significant main effect of race of the customer in the

scenario influencing the likelihood to call the police, β = -.24, 95% CI [-.822, .337],

t(282) = -.824, p = .41. Participants did not report a difference in the likelihood to call

the police based on race.

Research Question 2

Next, I examined whether participants who were more risk averse were more

likely to call the police. There was a significant main effect for risk perception and

likelihood to call the police, β = .66, 95% CI [.301, 1.028], t(282) = 3.594, p < .001

(Table 7: Block 2). Participants who were risk averse were more likely to call the police.

Research Question 3

Then, I examined the interaction of risk perception and the race of the customer.

There was not a significant interaction of risk perception and race of the customer on the

likelihood to call the police, β = .01, 95% CI [-.679, .705], t(282) = .037, p = .970 (Table

7: Block 3).

44

Tab

le 7

The

Lik

elih

ood t

o C

all

Poli

ce

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

288.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith w

hit

e =

0 a

nd

1 =

bla

ck.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on

sca

le a

nd r

ace

of

the

cust

om

er, ca

lcula

ted b

y m

ult

iply

ing r

isk p

erce

pti

on a

nd

race

of

the

cust

om

er.

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

B (

SE

)

R2

R2

chan

ge

F c

han

ge

T

ole

rance

Lik

elih

ood t

o

Cal

l P

oli

ce

Blo

ck 1

.040

.040

5.9

51**

A

ge

-.01 (

.01)

.9

58

G

ender

-1

.06 (

.31)*

**

.958

B

lock

2

.0

86

.046

7.0

99***

A

ge

-.02 (

.01)

.9

48

G

ender

-.

74 (

.31)*

.882

R

ace

-.

24 (

.29)

.9

92

R

isk

.66 (

.19)*

**

.894

B

lock

3

.0

86

.000

.001

A

ge

-.02 (

.01)

.9

48

G

ender

-.

74 (

.32)*

.882

R

ace

-.

24 (

.30)

.9

92

R

isk

.66 (

.25)*

*

.4

78

In

tera

ctio

n:

Ris

k*R

ace

.01 (

.35)

.5

08

45

Overall, women compared to men were more likely to call the police, and risk

averse individuals compared to risk seeking individuals were more likely to call the

police.

Examining Gender: Linear Regression

To avoid redundancy, the control variables block including age and gender was

removed. First, the variables, age, gender, race of the customer in the scenario, and risk

perception were added to the model, [R2 = .086, R2adj = .073, F(4, 283) = 6.652, p < .001].

The addition of interaction term between risk perception and gender did not add

significantly to regression model, [R2 = .094, R2adj = .070, F(6, 281) = 1.218, p = .30]. [R2

= .040, R2adj = .033, F(2, 285) = 5.951, p < .01]

In the previous model (Table 7: Block 2), women were more likely to call the

police compared to men; thus, only the interaction term between risk perception and

gender are explored. There was not a significant interaction of risk perception and gender

on the likelihood to call the police, β = -.58, 95% CI [-1.312, .152], t(281) = -1.560, p =

.12 (Table 8: Block 2).

46

Tab

le 8

The

Infl

uen

ce o

f G

end

er o

n t

he

Lik

elih

ood t

o C

all

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

B (

SE

)

R2

R2

chan

ge

F

chan

ge

Tole

rance

Lik

elih

ood t

o

Cal

l P

oli

ce

Blo

ck 1

.086

.086

6.6

52*

**

A

ge

-.02 (

.01)

.9

48

G

ender

-.

74 (

.31)*

.882

R

ace

-.

24 (

.29)

.9

92

R

isk

.66 (

.19)*

**

.894

B

lock

2

.0

94

.008

1.2

18

A

ge

-.02 (

.01)

.9

47

G

ender

-.

70 (

.32)*

.877

R

ace

-.

24 (

.29)

.9

92

R

isk

1.0

0 (

.34)*

*

.2

73

In

tera

ctio

n:

Ris

k*R

ace

.004 (

.35)

.4

05

In

tera

ctio

n:

Ris

k*G

ender

-.

58 (

.37)

.5

08

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

288.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on s

cale

and r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

.

47

Overall, women compared to men were more likely to call the police, and risk

averse individuals compared to risk seeking individuals were more likely to call the

police.

Examining Political Orientation: Linear Regression

To avoid redundancy, the control variables block including age and gender was

removed. First, the variables age, gender, race of the customer in the scenario, risk

perception, and political orientation were added to the model, [R2 = .123, R2adj = .108,

F(5, 282) = 6.652, p < .001]. The addition of the interaction term risk perception and

political orientation did not add significantly to the regression model, [R2 = .131, R2adj =

.106, F(8, 279) = .821, p = .48].

There was a significant main effect of political orientation, β = -.47, 95% CI [-

.737, 977], t(282) = -3.461, p < .001 (Table 9: Block 1). Liberals were less likely to call

the police compared to conservatives. There was not a significant interaction of risk

perception and political orientation on the likelihood to call the police, β = -.15, 95% CI

[-1.312, .152], t(282) = -.949, p = .34.

48

Tab

le 9

The

Infl

uen

ce o

f P

oli

tica

l O

rien

tati

on o

n t

he

Lik

elih

ood t

o C

all

Poli

ce

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

288.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to

the

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on s

cale

and r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

. In

tera

ctio

n R

isk*P

O i

ncl

udes

ris

k p

erce

pti

ons

scal

e an

d

poli

tica

l ori

enta

tion

.

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

B (

SE

)

R2

R2

chan

ge

F c

han

ge

T

ole

rance

Lik

elih

ood t

o

Cal

l P

oli

ce

Blo

ck 1

.123

.123

7.9

25*

**

A

ge

-.02 (

.01)

.9

35

G

ender

-.

83 (

.31)*

.875

R

ace

-.

02 (

.30)

.9

45

R

isk

.62 (

.18)*

**

.890

P

O

-.47 (

.14)*

**

.932

B

lock

2

.1

31

.008

.821

A

ge

-.02 (

.01)

.9

34

G

ender

-.

77 (

.31)*

*

.8

62

R

ace

-.

03 (

.30)

.9

45

R

isk

.86 (

.33)*

*

.2

65

P

O

-.46 (

.14)*

**

.918

In

tera

ctio

n:

Ris

k*R

ace

.05 (

.36)

.4

75

In

tera

ctio

n:

Ris

k*G

ender

-.

44 (

.37)

.4

00

In

tera

ctio

n:

Ris

k*P

O

-.15 (

.15)

.9

23

49

Overall, women compared to men were more likely to call the police, risk averse

participants compared to risk seeking participants were more likely to call the police, and

conservatives were more likely to call the police compared to liberals.

Logistic Regression: Call Police

Further, to assess the research questions, I also completed two logistic regressions

based on the questions: “Based on the scenario you previously read, would you call the

police?” and “If someone else saw the same scenario as you and they decided to call the

police, do you agree or disagree with that choice?” For each research question, these two

items’ results are presented in this sequential order as “Call Police” and “Someone Else

Call Police.”

Results indicated that the overall fit of the five predictors (age, gender, race, risk

perception, and the interaction term: risk*race) was questionable due to a high -2 Log

likelihood score, -2 Log likelihood = 362.974 (a perfect model would have a -2 Log

Likelihood score of 0 as defined by Mertler & Vannatta, 2013), but the -2 Log Likelihood

was statistically reliable in distinguishing between the predictors [2(5) = 13.979, p =

.02]. The model correctly classified 63.8% of the cases. Further, the correlation matrix

(Table 10) suggests that a majority of the variables are not strongly intercorrelated, which

suggests that the regression is reliable. Risk perception and the interaction between risk

and race, however, were strongly related, (r = -.66).

50

Table 10

Correlation Matrix: The Choice to Call Police

Age Gender Race Risk

Gender .19

Race -.03 .03

Risk -.08 .20 .10

Interaction: Risk*Race .02 .00 -.09 -.66

Note. n = 287. Race refers to the race of the customer in the scenario; dummy coded with

white = 0 and 1 = black.

Risk refers to risk perception: a higher score indicates risk aversion and a lower score

indicates risk seeking; the variable was mean centered.

Interaction Risk* Race includes risk perception scale and race of the customer, calculated

by multiplying risk perception and race of the customer.

Research Question 1

First, I examined whether race was a significant predictor in the choice to call the

police. As shown in Table 11, Block 2, using the Wald chi-square statistic to test the

individual regression coefficients (Peng, Lee, & Ingersoll, 2002), race was not a

significant predictor in the choice to call the police, β = -.15, p = .56. Race did not affect

the choice to call the police.

Research Question 2

Next, I examined whether risk perception was a significant predictor in the choice

to call the police. As shown in Table 11, Block 2 risk perception was a significant

predictor in the choice to call the police, β = .34, p = .04. Participants who were risk

averse were more likely to call the police.

51

Research Question 3

Then, I examined the interaction of risk perception and the race of the customer to

predict the choice to call the police. There was not a significant interaction of risk

perception and race of the customer on the choice to call the police, β = .26, p = .69

(Table 11: Block 3).

52

Tab

le 1

1

The

Cho

ice

to C

all

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e β

(Odds

Rat

io)

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.01 (

.01)

1.3

6

1

.24

0.9

87

G

ender

-.

71 (

.26)*

*

7.6

5

1

.01

2.0

25

B

lock

2

A

ge

-.02 (

.01)

1.7

7

1

.18

0.9

85

G

ender

-.

55 (

.27)*

4.2

4

1

.04

1.7

33

R

ace

-.

15 (

.25)

.335

1

.56

1.1

57

R

isk

.34 (

.16)*

4.4

0

1

.04

1.4

08

B

lock

3

A

ge

-.02 (

.01)

.011

1

.19

0.9

85

G

ender

-.

55 (

.28)*

.2

67

1

.04

1.7

33

R

ace

-.

16 (

.26)

.253

1

.52

1.1

78

R

isk

.22(.

30)

.216

1

.31

1.2

48

In

tera

ctio

n:

Ris

k*R

ace

.26 (

.31)

.314

1

.41

1.2

97

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

287.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith w

hit

e =

0 a

nd 1

= b

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on

sca

le a

nd r

ace

of

the

cust

om

er, ca

lcu

late

d b

y m

ult

iply

ing r

isk p

erce

pti

on a

nd

race

of

the

cust

om

er.

53

Overall, the model predicted that risk averse individuals compared to risk seeking

individuals chose to call the police more and women compared to men chose to call the

police more.

Examining Gender: Logistic Regression (Call Police)

Results indicated that the overall fit of the six predictors (age, gender, race of the

customer, risk perception, the interaction term: risk*race, and the interaction term:

risk*gender) was questionable due to a high -2 Log likelihood score, -2 Log likelihood =

359.847, but the -2 Log likelihood was statistically reliable in distinguishing between the

predictors [2(6) = 17.106, p = .01]. The model correctly classified 63.4% of the cases.

Further, the correlation matrix (Table 12) suggests that a majority of the variables are not

strongly intercorrelated, which suggests that the regression is reliable. Risk perception

and the interaction between risk and race (r = -.48) and the interaction between risk and

gender (r = -.69), however, does have a strong correlation.

54

Table 12

Correlation Matrix: Gender and the Choice to Call Police

Age Gender Race Risk Interaction:

Risk*Race

Gender .18

Race -.03 .02

Risk -.10 .28 .07

Interaction:

Risk*Race

.02 -.15 -.06 -.48

Interaction:

Risk*Gender

.06 .01 -.02 -.69 .02







Interaction Risk*Gender includes risk perception scale and gender, calculated by

multiplying risk perception and race of the customer.

In a previous model (Table 11: Block 2), women were more likely to call the


gender are explored. There was not a significant interaction of risk perception and gender

on the likelihood to call the police, β = -.59, p = .08 (Table 13: Block 2).

55

Tab

le 1

3

The

Infl

uen

ce o

f G

end

er o

n t

he

Choic

e to

Call

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e β

(Odds

Rat

io)

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.02 (

.01)

1.7

7

1

.18

0.9

85

G

ender

-.

55 (

.27)

*

4.2

4

1

.04

1.7

33

R

ace

-.

15 (

.25)

.34

1

.56

1.1

57

R

isk

.34 (

.16)

*

4.4

0

1

.04

1.4

08

B

lock

2

A

ge

-.02 (

.01)

1.9

63

1

.16

0.9

84

G

ender

-.

49 (

.28)

3.0

52

1

.08

1.6

26

R

ace

-.

16 (

.25)

.375

1

.54

1.1

68

R

isk

.57 (

.30)

3.5

42

1

.06

1.7

69

In

tera

ctio

n:

Ris

k*R

ace

.24 (

.31)

.593

1

.44

1.2

72

In

tera

ctio

n:

Ris

k*G

ender

-.

59 (

.34)

3.0

25

1

.08

0.5

54

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

287.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on s

cale

and r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

.

56

Overall, the model predicted that women compared to men chose to call the police

more and risk averse individuals compared to risk seeking individuals chose to call the

police more.

Examining Political Orientation: Logistic Regression (Call Police)

Results indicated that the overall fit of the eight predictors (age, gender, race of the

customer, PO, risk perception, the interaction term: risk*race, the interaction term:

risk*gender, and the interaction term: risk*PO) was questionable (-2 Log likelihood =

357.978; Mertler & Vannatta, 2013), but the -2 Log likelihood was statistically reliable in

distinguishing between the predictors [2(8) = 18.974, p = .015]. The model correctly

classified 64.1% of the cases. Further, the correlation matrix (Table 14) suggests that a

majority of the variables are not strongly intercorrelated, which suggests that the

regression is reliable. Risk perception and the interaction between risk and race (r = -.50)

and the interaction between risk and gender (r = -.69), however, does have a strong

correlation.

57

Table 14

Correlation Matrix: Political Orientation and the Choice to Call Police

Age Gender Race Risk PO Interaction:

Risk*Race

Interaction:

Risk*Gender

Gender .19

Race -.05 -.00

Risk -.09 -.26 .05

PO .12 -.11 -.21 .07

Interaction:

Risk*Race

.02 -.02 -.06 -.50 .04

Interaction:

Risk*Gender

.05 -.14 .00 -.69 -.07 .03

Interaction:

Risk*PO

-.00 -.05 .03 .14 -.00 -.21 -.04




indicates risk seeking; the variable was mean centered. PO refers to political orientation:

a higher score indicates liberal ideology and a lower score conservative ideology.




multiplying risk perception and race of the customer. Interaction Risk*PO includes risk

perception scale and political orientation, calculated by multiplying risk perception and

race of the customer.

There was not a significant main effect of political orientation, β = -.17, p = .16

(Table 15: Block 1). There were no political orientation differences in the choice to call

the police. There was not a significant interaction of risk perception and political

orientation on the likelihood to call the police, β = -.09, p = .52.

.

58

Tab

le 1

5

The

Infl

uen

ce o

f P

oli

tica

l O

rien

tati

on o

n t

he

Choic

e to

Call

Poli

ce

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

287.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

PO

(poli

tica

l ori

enta

tion)

refe

rs t

o p

oli

tica

l ori

enta

tion v

aria

ble

that

was

co

mpute

d f

rom

4 i

tem

s an

d w

as m

ean c

ente

red.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on s

cale

and r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

.

Inte

ract

ion R

isk*P

O i

ncl

udes

ris

k p

erce

pti

on s

cale

and p

oli

tica

l ori

enta

tio

n.

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e β

(Odds

Rat

io)

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.02 (

.01)

2.1

74

1

.14

0.9

83

G

ender

-.

58 (

.27)*

4.6

94

1

.03

1.7

92

R

ace

-.

07 (

.26)

.075

1

.78

1.0

73

R

isk

.33 (

.16)*

3.9

48

1

.05

1.3

86

P

O

-.17 (

.12)

1.9

44

1

.16

0.8

47

B

lock

2

A

ge

-.02 (

.01)

2.2

89

1

.13

0.9

83

G

ender

-.

51 (

.28)

3.3

10

1

.07

1.6

65

R

ace

-.

10 (

.26)

.140

1

.71

1.1

02

R

isk

.51 (

.31)

2.8

01

1

.09

1.6

71

P

O

-.15 (

.12)

1.4

27

1

.23

0.8

65

In

tera

ctio

n:

Ris

k*R

ace

.27 (

.32)

.709

1

.40

1.3

09

In

tera

ctio

n:

Ris

k*G

ender

-.

55 (

.34)

2.5

84

1

.11

0.5

79

In

tera

ctio

n:

Ris

k*P

O

-.09 (

.14)

.416

1

.52

0.9

14

59

Overall, women chose to call the police more than men and risk averse

individuals chose to call the police more than risk seeking individuals.

Logistic Regression: Someone Else Call Police

Results indicated that the overall fit of the five predictors (age, gender, race, risk

perception, and the interaction term: risk*race) was questionable (-2 Log likelihood =

364.142), but the -2 Log likelihood was statistically reliable in distinguishing between the

predictors [2(5) = 15.882, p < .001]. The model correctly classified 65.3% of the cases.



and the interaction between risk and race (r = -.67), however, does have a strong

correlation.

Further, the correlation matrix (Table 14) suggests that a majority of the variables are

not strongly intercorrelated, which suggests that the regression is reliable. Risk

perception and the interaction between risk and race (r = -.50) and the interaction

between risk and gender (r = -.69), however, does have a strong correlation.

Table 16

Correlation Matrix: Someone Else’s Decision to Call Police

Age Gender Race Risk

Gender .19

Race -.04 .01

Risk -.11 .19 .01

Interaction: Risk*Race .01 .01 .10 -.67







60

Research Question 1

First, I assessed whether race was a significant predictor in the agreement with

someone else’s decision to call the police. As shown in Table 17, Block 2, again, using

the Wald chi-square statistic to test the individual regression coefficients (Peng et al.,

2002), race was not a significant predictor in the agreement with someone else’s decision

to call the police, β = -.02, p = .93. Race did not affect the agreement with someone else’s

decision to call the police.

Research Question 2

Next, I examined whether risk perception was a significant predictor in the

agreement with someone else’s decision to call the police. Risk perception was a

significant predictor in the agreement with someone else’s decision to call the police, (β =

.47, p = .003; Table 17: Block 2). Risk averse individuals were more likely to agree with

someone else’s decision to call the police.

Research Question 3

Lastly, for my main analyses, I examined the interaction of risk perception and the

race of the customer to predict the agreement with someone else’s decision to call the

police. There was not a significant interaction of risk perception and the race of the

customer regarding the agreement with someone else’s decision to call the police, (β =

.21, p = .49; Table 17: Block 3).

61

Tab

le 1

7

Som

eone

Els

e’s

Dec

isio

n t

o C

all

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e

β

(Odds

Rat

io)

Som

eone

Els

e

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.02 (

.01)

2.3

2

1

.13

0.9

84

G

ender

-.

59 (

.26)*

5.1

6

1

.02

1.7

97

B

lock

2

A

ge

-.02 (

.01)

3.3

1

1

.07

0.9

79

G

ender

-.

38 (

.28)

1.9

4

1

.16

1.5

50

R

ace

-.

02 (

.26)

.008

1

.93

1.0

78

R

isk

.47 (

.16)*

*

8.5

9

1

.00

1.5

85

B

lock

3

A

ge

-.02 (

.01)

3.2

9

1

.07

0.9

80

G

ender

-.

38 (

.27)

1.9

5

1

.16

1.4

59

R

ace

-.

01 (

.25)

.00

1

.98

1.0

06

R

isk

.37 (

.22)

2.8

5

1

.09

1.4

41

In

tera

ctio

n:

Ris

k*R

ace

.21 (

.30)

.48

1

.49

1.2

34

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

288.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith w

hit

e =

0 a

nd

1 =

bla

ck.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk*

Rac

e in

cludes

ris

k p

erce

pti

on

sca

le a

nd r

ace

of

the

cust

om

er, ca

lcula

ted b

y m

ult

iply

ing r

isk p

erce

pti

on a

nd

race

of

the

cust

om

er.

62

Overall, the model predicted that risk averse individuals compared to risk seeking

individuals agreed more with someone else’s decision to call the police, and that women

compared to men agreed more with someone else’s decision to call the police.

Examining Gender: Logistic Regression (Someone Else Call Police)

Results indicated that the overall fit of the six predictors (age, gender, race of the

customer, risk perception, the interaction term: risk*race, and the interaction term:

risk*gender) was questionable due to a high -2 Log likelihood score, -2 Log likelihood =

358.405, but the -2 Log likelihood was statistically reliable in distinguishing between the

predictors [2(6) = 21.619, p < .001]. The model correctly classified 66.7% of the cases.



and the interaction between risk and race (r = -.50) and the interaction between risk and

gender (r = -.71), however, does have a strong correlation.

63

Table 18

Correlation Matrix: Gender and Someone Else’s Decision to Call Police

Age Gender Race Risk Interaction:

Risk*Race

Age

Gender -.20

Race -.04 .01

Risk -.12 .12 -.01

Interaction:

Risk*Race

.01 .00 .12 -.48

Interaction:

Risk*Gender

.06 -.01 -.01 -.71 .00








multiplying risk perception and race of the customer.

In a previous model (Table 17: Block 1), women were more likely to call the


gender are explored. There was a significant interaction of risk perception and gender on

the agreement with someone else’s decision to call the police, β = -.59, p = .08 (Table 19:

Block 2). The interaction effects were examined through using a median split to create a

risk seeking and risk averse group. This method has been adopted in other studies (e.g.,

Peters, & Bjalkebring, 2015; Peters et al., 2009; Peters, Sol Hart, Tusler, & Fraenkel,

2014). Risk averse women compared to risk seeking women were more likely to agree

with someone else’s decision to call the police, whereas men who were risk seeking and

64

risk averse agreed with someone else’s decision to call the police similarly. Further, risk

averse women agreed more with someone else’s decision to call the police than risk

averse men overall. (Figure 1).

65

Tab

le 1

9

The

Infl

uen

ce o

f G

end

er o

n t

he

Agre

emen

t w

ith S

om

eone

Els

e’s

Dec

isio

n t

o C

all

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e β

(Odds

Rat

io)

Som

eone

Els

e

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.02 (

.01)

3.3

1

1

.07

0.9

80

G

ender

-.

38 (

.27)

1.9

4

1

.16

0.6

86

R

ace

-.

02 (

.25)

.008

1

.93

0.9

77

R

isk

.47 (

.16)

**

8.5

9

1

.00

1.5

97

B

lock

2

A

ge

-.02 (

.01)

3.6

0

1

.07

0.9

57

G

ender

.3

8 (

.27)

1.8

8

1

.16

1.4

56

R

ace

.0

0 (

.25)

.00

1

.98

0.9

98

R

isk

.86 (

.22)

7.4

9

1

.09

2.3

59

In

tera

ctio

n:

Ris

k*R

ace

.20 (

.31)

.427

1

.52

1.2

27

In

tera

ctio

n:

Ris

k*G

ender

-.

79 (

.34)*

5.4

55

1

.02

0.4

55

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

Inte

ract

ion R

isk*R

ace

incl

udes

ris

k p

erce

pti

on a

nd r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

.

66

Interaction between Gender and Risk Perception on the Agreement with Someone Else’s


Figure 1. Bars indicate standard errors.

67

Overall, the model showed that risk averse individuals compared to risk seeking

individuals agreed more with someone else’s decision to call the police. Additionally,

women who were risk averse compared to risk seeking agreed more with someone else’s

decision to call the police. Further, risk averse and risk seeking men agreed with someone

else’s decision to call the police similarly.

Examining Political Orientation: Logistic Regression (Someone Else Call Police)

Results indicated that the overall fit of the eight predictors (age, gender, race of

the customer, PO, risk perception, the interaction term: risk*race, the interaction term:

risk*gender, and the interaction term: risk*PO) was questionable (-2 Log likelihood =

357.978; Mertler & Vannatta, 2013), but the -2 Log likelihood was statistically reliable in

distinguishing between the predictors [2(8) = 18.974, p = .015]. The model correctly

classified 64.1% of the cases. Further, the correlation matrix (Table 20) suggests that a

majority of the variables are not strongly intercorrelated, which suggests that the

regression is reliable. Risk perception and the interaction between risk and race (r = -.47)

and the interaction between risk and gender (r = -.70), however, does have a strong

correlation.

68

Table 20

Correlation Matrix: Political Orientation and the Agreement with Someone Else’s

Decision to Call Police

Age Gender Race Risk PO Interaction:

Risk*Race

Interaction:

Risk*Gender

Age

Gender .20

Race -.07 -.04

Risk -.11 .10 .01

PO .14 .13 -.24 .01

Interaction:

Risk*Race

.03 -.01 .15 -.47 -.05

Interaction:

Risk*Gender

.04 .01 -.03 -.70 -.04 -.02

Interaction:

Risk*PO

.02 -.04 -.06 -.01 -.26 -.25 .06




indicates risk seeking; the variable was mean centered. PO refers to political orientation:

a higher score indicates liberal ideology and a lower score conservative ideology.




multiplying risk perception and race of the customer. Interaction Risk*PO includes risk

perception scale and political orientation, calculated by multiplying risk perception and

race of the customer.

There was a significant main effect of political orientation, β = -.29, p = .02

(Table 21: Block 1). Liberals were less likely to agree with someone else’s decision to

call the police compared to conservatives. There was also a significant interaction of risk

perception and political orientation on the agreement with someone else’s decision to call

69

the police, β = -.34, p < .001. The interaction effects were examined through using a

median split to create a risk seeking and risk averse group. This method has been adopted

in other studies (e.g., Peters, & Bjalkebring, 2015; Peters et al., 2009; Peters et al., 2014).

Political orientation was split into two separate categories: political conservative and

political liberal. Participants who reported to be “Very Conservative” or “Conservative

were considered conservative, whereas participants who reported to be “Liberal” or

“Very Liberal” were considered liberal. This method has been adopted in other studies

(e.g., Champion, 1987; Cutshall & Adams, 1983; Wilbanks & Kim, 1984). Conservatives

who were risk averse were more likely to agree with someone else’s decision to call the

police than risk seeking conservatives, whereas for liberals, risk perceptions did not affect

agreement with someone else’s decision to call the police similarly (Figure 2).

70

Tab

le 2

1

The

Infl

uen

ce o

f P

oli

tica

l O

rien

tati

on o

n t

he

Agre

emen

t w

ith S

om

eone

Els

e’s

Dec

isio

n t

o C

all

Poli

ce

Outc

om

e

Var

iable

Blo

cks

& V

aria

ble

s

β (

SE

β)

Wald

’s

2

df

p

e β

(Odds

Rat

io)

Cal

l P

oli

ce

Blo

ck 1

A

ge

-.02 (

.01)*

4.3

86

1

.04

0.9

77

G

ender

-.

44 (

.28)

2.6

16

1

.11

0.6

41

R

ace

.1

1 (

.26)

.189

1

.66

1.1

20

R

isk

.45 (

.16)*

*

7.8

53

1

.01

1.5

75

P

O

-.29 (

.12)*

5.4

16

1

.02

0.7

52

B

lock

2

A

ge

-.03 (

.01)*

4.4

90

1

.03

0.9

76

G

ender

-.

41 (

.28)

2.1

58

1

.14

0.6

62

R

ace

.1

6 (

.27)

.349

1

.56

1.1

73

R

isk

.79 (

.32)*

6.0

19

1

.01

2.1

94

P

O

-.33 (

.13)*

6.2

53

1

.01

0.7

20

In

tera

ctio

n:

Ris

k*R

ace

.38 (

.33)

1.2

93

1

.26

1.4

58

In

tera

ctio

n:

Ris

k*G

ender

-.

74 (

.35)*

4.6

36

1

.03

0.4

76

In

tera

ctio

n:

Ris

k*P

O

-.34 (

.15)*

*

4.9

66

1

.03

0.7

14

Note

. ***:

p <

.001;

**:

p <

.01;

*:

p <

.05. n =

288.

Gen

der

: dum

my c

oded

wit

h f

emal

e =

0 a

nd m

ale

= 1

.

Rac

e re

fers

to t

he

race

of

the

cust

om

er i

n t

he

scen

ario

; dum

my c

od

ed w

ith W

hit

e =

0 a

nd 1

= B

lack

.

Ris

k r

efer

s to

ris

k p

erce

pti

on:

a hig

her

sco

re i

ndic

ates

hig

her

ris

k a

ver

sion a

nd a

low

er s

core

indic

ates

ris

k s

eekin

g;

the

var

iable

was

mea

n c

ente

red.

PO

(poli

tica

l ori

enta

tion)

refe

rs t

o p

oli

tica

l ori

enta

tion v

aria

ble

that

was

com

pute

d f

rom

4 i

tem

s

and w

as m

ean

cen

tere

d.

A h

igher

sco

re i

ndic

ates

lib

eral

ideo

log

y a

nd a

low

er s

core

indic

ates

conse

rvat

ive

ideo

log

y.

Inte

ract

ion R

isk* R

ace

incl

udes

ris

k p

erce

pti

on s

cale

and r

ace

of

the

cust

om

er.

Inte

ract

ion R

isk*G

ender

incl

udes

ris

k p

erce

pti

on s

cale

and g

ender

.

Inte

ract

ion R

isk*P

O i

ncl

udes

ris

k p

erce

pti

on s

cale

and p

oli

tica

l ori

enta

tio

n.

71

Interaction between PO and Risk Perception on the Agreement with Someone Else’s


Figure 2. Bars indicate standard errors.

Overall, risk averse participants agreed more with someone else’s decision to call

the police than risk seeking individuals and conservatives agreed more with someone

else’s decision to call the police than liberals. Additionally, risk averse women agreed

more with someone else’s decision to call the police than risk seeking women, whereas

there were no differences based on risk preferences for men. Conservatives agreed more

72

with someone else’s decision to call the police than those who were risk seeking, whereas

there were no differences based on risk preferences for liberals.

Mediation Analysis

I examined whether risk perception mediated the relationship between race of

customer and choice to call the police (i.e., dichotomous variable). I conducted four steps

to examine mediation (Baron & Kenny, 1986). First, the regression of race of the

customer on the choice to call the police, ignoring the mediator, was not significant, b =

.02, t(293) = .373, p = .71. Next, the regression of the race of the suspect on the mediator,

risk perception, was also not significant, b = .13, t(293) = 1.340, p = .18. Then the

mediation process showed that risk perception, controlling for the race of the customer,

was significant, b = .12, t(293) = 3.658, p < .001. Then analyses revealed that controlling

for risk perception, race of suspect was not a significant predictor of the choice to call the

police, b = -1.54, t(293) = .094, p = .93. A Sobel test (Preacher & Leonardelli, 2001) was

conducted and found no mediation in the model (z = 1.25, p = .21; Figure 3). In

summary, these four steps illustrated that there was no evidence of mediation within the

model.

73

Mediation Model

Figure 3. *** p < .001. Race of Customer = independent variable; Risk Perception =

mediator; Choice to Call Police = Dependent Variable. n = 294.

Risk

Perception

Choice to

Call Police

Race of

Customer

a = .13 b = .12***

c = .02 (c’ = .12)

74

CHAPTER 5.

DISCUSSION

Summary of Results

Race of the customer (i.e., black or white) in the scenario did not influence the

likelihood to call the police, whether participants would call the police, or agreement with

someone else’s choice to call the police. Regardless of race, individuals who were risk

averse reported a higher likelihood to call the police, reported more often that they would

call the police, and agreed more with someone else’s decision to call the police. Taken

together, the race of the perceived suspect and the assessment of perceived risk (i.e., risk

aversion) did not influence the likelihood to call the police, whether participants would

call the police, or their agreement with someone else’s choice to call the police.

Women reported a higher likelihood to call the police, reported more often that they

would call the police, and agreed more with someone else’s decision to call the police

than men. Risk averse women, compared to risk seeking women, agreed more with

someone else’s decision to call the police. Also, conservatives reported a higher

likelihood to call the police, reported more often that they would call the police, and

agreed more with someone else’s decision to call the police than liberals. Risk averse

conservatives, compared to risk seeking conservatives, agreed more with someone else’s

decision to call the police.

Race

Across all analyses, race of the perceived suspect (i.e., the customer in the

scenario) was not influential in the reported likelihood to call the police, whether

75

participants would call the police, and their agreement with someone else’s choice to call

the police. News reports of calls made to the police (e.g., a student napping in a dorm

common area; Griggs, 2018) could be isolated incidents given the amount of 911 calls

received (an estimated 240 million calls made to 911 each year; “9-1-1 Statistics,” 2017).

Publicized news reports of black individuals having the police called on them could

create an availability heuristic. An availability heuristic suggests that a person judges the

occurrence of events by the ease of retrieval of relevant examples (Tversky & Kahneman,

1973). For instance, videos taken by the student who was napping in a dorm common

space received over a million views (one of the videos a million and a half views) and

was mentioned on the popular show, The Daily Show with Trevor Noah (Noah, 2018).

Perhaps, due to these publicized reports, the frequency of calls to police on black

individuals for seemingly harmless activities comes to mind easily; however, this

availability heuristic could be biasing the reality of the frequency of these calls.

One explanation for the ineffectiveness of race to influence the reported

likelihood to call the police, whether participants would call the police, and their

agreement with someone else’s choice to call the police could be that the sample used

might not have had biased attitudes toward black individuals. Although mTurk

populations are similar to the demographic characteristics of aversive racists (e.g., liberal,

well-educated, and white; Dovidio & Gaertner, 2000; Huff & Tingley, 2015; Levay,

Freese, & Druckman, 2016; Nail et al., 2003), there was no evidence for aversive racism

in the current study. Thus, the current sample might not have had biased attitudes toward

76

black individuals. The study sample was only 74% white, and racial/ethnic minorities

may not hold the same biases against black individuals.

Another possibility is that the customer being identified briefly as a young black

or white male through a text description might not have been enough to influence the

likelihood to call the police, whether participants would call the police, and their

agreement with someone else’s choice to call the police. The young black male

stereotype of delinquency and criminality (Steffensmeier, Ulmer, & Kramer, 1998) might

not have been aroused in the scenario. The use of images to represent the customer in the

scenario might have been more effective in representing the demographic characteristics

(i.e., race) of the customer. For instance, judges see and interact with a defendant before a

decision is made regarding incarceration and sentencing. Judges, like U.S. citizens, can

fall victim to stereotypes, perceiving young, black men as more dangerous, involved in

street life, and less reformable (Daly, 1994) Thus, simply reading a scenario might not

have aroused real-life feelings and attitudes of a perceived suspect (i.e., the customer in

the scenario).

Despite race remaining a highly charged topic in society (Suchet, 2004), these

results suggest that in this study, race was not influential in the reported likelihood to call

the police, whether participants would call the police, and their agreement with someone

else’s choice to call the police. Further, the race of the perceived suspect and risk

perception (i.e., risk aversion) did not influence the likelihood to call the police, whether

participants would call the police, or their agreement with someone else’s choice to call

the police.

77

Risk Perception

Risk averse participants compared to risk seeking participants had a higher reported

likelihood to call the police, would call the police more, and agreed more with someone

else’s decision to call the police. This finding highlights that risk perception fosters an

individual assessment of a situation (Sitkin & Pablo, 1992). Prior evidence has revealed

that risk perception invokes two methods for assessment: risk as feelings (instinctive

reactions to danger) and risk as an analysis (logical reactions to danger). Risk is often

evaluated through intuitive feelings, automatically, and handled quickly (i.e., risk as

feelings; Slovic & Peters, 2006). Thus, an evaluation based on feelings, intuition, and

instinctive reactions to danger further supports how individualistic the assessment of risk

perception is in a risk situation. In a possible crime situation, calling the police could

provide a sense of security in a perceived uncertain situation. Thus, calling the police

might not be a decision that is based solely on another person (i.e., offender), but on the

personal assessment of the situation and fear of the caller. Ultimately, the decision to call

the police is personal, and is based on a subjective evaluation of a situation.

Gender

Women compared to men had a higher reported likelihood to call the police,

reported more often that they would call the police, and agreed more with someone else’s

decision to call the police. This finding is consistent with previous research (Eith &

Durose, 2011). Women compared to men are more likely to contact the police, report a

crime, disturbances, and suspicious activity to police (Davis et al., 2018). Further, women

might have more contact with police because they have higher confidence in the police

78

than men (Apple & O’Brien, 1983; Cao et al., 1996). This might be because women have

different types of relationships with police than men. For women, contact with the police

is often less hostile, whereas for men, hostile contact (e.g., excessive police action) with

police is more common (Cao et al., 1996; Davis et al., 2018). Generally, compared to

men, women have more positive police contact and relationships, which could be

influential in their choices to contact police.

Women, compared to men, are more risk averse in numerous areas of life:

financial decision making (Jianakoplos & Bernasek, 1998), drug and alcohol choices

(Spigner et al., 1993), and gambling decisions (Levin, Synder, & Chapman, 2010).

Further, compared to men, women have a greater fear of crime (Stanko, 1995). Thus, it is

logical to extrapolate that having the police called brings a sense of certainty in an

uncertain possible crime situation for risk averse women. For instance, in the current

study, risk averse women agreed more with someone else’s decision to call the police.

Women being more risk averse might agree more with someone else’s decision to call the

police because it provides another sense of security and certainty in an uncertain

situation.

Political Orientation

Conservatives compared to liberals had a higher reported likelihood to call the

police, reported more often that they would call the police, and agreed more with

someone else’s decision to call the police. Conservatives, compared to liberals, typically

report having a high confidence in the police (Congressional Research Service, 2018;

79

Stack & Cao, 1998). This could be because political conservatives believe police

authority conveys conservative ideologies (Frimer, Gaucher, & Schaefer, 2014).

Further, research using the Moral Foundations Questionnaire (Graham et al.,

2011) suggests that liberals and conservatives have different considerations for moral

foundations (i.e., loyalty, purity, authority, fairness, and harm). In regard to the original

five foundations, political conservatives are more likely to endorse the binding

foundations (i.e., loyalty, purity, and authority), whereas political liberals are more likely

to endorse the individualizing foundations (i.e., fairness and harm; Graham et al., 2009).

The binding foundation of authority foundation invokes appeals to obedience and respect,

which is often observed in institutions of authority, such as a police department (Clifford,

Iyengar, Cabeza, & Sinnott-Armstrong, 2015). Thus, when making the decision to call

the police, political conservatives could exercise their moral beliefs by showing respect to

the laws and rules of an institutional authority.

Additionally, this study suggests that risk averse conservatives, compared to risk

seeking conservatives, agreed more with someone else’s decision to call the police. High

levels of confidence in the police could possibly explain why risk averse conservatives

are more likely to agree with someone else’s decision to call the police. Evidence has

shown that conservatives are more sensitive to fear (e.g., risk averse; Jost et al., 2003),

and with high confidence in the police (e.g., Congressional Research Service, 2018; Stack

& Cao, 1998), if someone made a call to police that might provide a sense of security and

certainty.

80

Limitations and Future Research

One potential limitation within this study is the scenario. The scenario was

author-generated and although it was pretested to address this possible limitation, it was

not perfect. The scenario used only two different combinations of race, age, and gender

(i.e., young black or white male) though a text-only description. Since the customer in the

scenario was not visible, characteristics of the customer could have been highlighted

more. For instance, other characteristics could have been added to the description of the

customer, such as wearing a hooded sweatshirt, wearing a suit, having tattoos, or baggy

pants. The racial characteristics of the customer could also have been highlighted with

use of pictures or other visual aids. Furthermore, manipulations of the race of the store

clerk might influence the motivation to call the police. Collectively, future research

should alter aspects of the scenario (e.g., using pictures), the suspect (e.g., wearing baggy

pants), and the actors in the scenario (e.g., a black store clerk) to examine their influence

on the motivation to call the police.

There are also some demographic limitations of the mTurk population. Although

mTurk provides more diversity than undergraduate populations, the demographic

variables on mTurk are often different than the U.S. populations (Ross, Irani, Silberman,

Zaldivar, & Tomlinson, 2010). For example, the mTurk population often has lower

income, higher education, and consists of smaller percentages of minority populations

compared to the national average (Huff & Tingley, 2015). Future research should explore

different samples and continue to examine mTurk populations to examine motivation to

81

call the police. Examining different sample populations will allow there to be greater

external validity of understanding the motivation to call the police.

Implications

This study examined an exploratory approach to understand the motivation to call

the police through aversive racism theory (Gaertner & Dovidio, 1986) and risk averse

motivation (Kahneman & Tversky, 1982). According to aversive racism theory, an

aversive racist would have potentially rationalized a call to police in an ambiguous

situation if the customer was black compared to white. According to risk averse

motivation, after an assessment of the situation, a risk averse individual would have

potentially been motivated to call the police to provide a sense of certainty in an

uncertain situation. The race of the customer in the scenario (i.e., perceived suspect) did

not influence the reported likelihood to call the police, whether participants would call

the police, or their agreement with someone else’s choice to call the police. Risk averse

participants, however, reported a higher likelihood to call the police, would call the police

more, and agreed more with someone else’s decision to call the police than risk seeking

participants. The current study adds to a preliminary start of the examination of aversive

racism theory and risk averse motivation in relation to decision to call the police. Further,

the current study draws attention to the limitation that there is no available information

regarding the demographic characteristics of police callers.

Practical implications include the need to educate 911 dispatch operators and 911

callers to enhance the use of police resources and time. Depending on the assessment of a

situation, there are varying degrees of what constitutes a need for police resources. With

82

an execution of questions asked to 911 callers, however, police resources could be

potentially saved from a situation where these resources are not needed.

Further, 911 education is not a required subject within United States school

systems. It is important that children learn at a young age the resources that calling police

provides. A 911 education could help ensure appropriate use of this privilege for both

children and adults. Although perceived risk is subjective, a general education on right-

and-wrong instances to use 911 is informative on ensuring accurate and professional use.

For example, on Nextdoor.com, which is used as platform for neighborhood contact on

various topics (i.e., finding a local plumber, neighborhood events), reports of a

“suspicious black man” were surfacing. To reduce this racial profiling, rather than

instantly being able to post “suspicious black man,” on the site, Nextdoor users were

asked to slow down in their observation, to identity actual suspicious behavior, and then

be specific about what the person looks like to avoid putting all black people in the same

category. Slowing down and thinking about what people were posting helped reduce

racial profiling by 75% on the website (Eberhardt, 2019). Extrapolating this concept,

slowing down and taking notice of the details of an event that could motivate a call to the

police could help individuals recognize potentially biased calls or unnecessary calls of

when police resources are truly not needed.

In the current study, the race of a perceived suspect (i.e., the customer in the

scenario) did not influence the decision to call the police, but race as a potential influence

in the decision to call the police should not be ignored from further exploration. There are

many disparities that exist between minority and majority groups, such as arrest and

83

incarceration rates. Thus, it is necessary to explore and understand why these disparities

exist to find solutions.

Conclusion

In this study, it is evident that the race of a suspect involved in a possible crime

was not influential, whereas the individual variability in risk perception did affect the

reported likelihood to call the police, whether participants would call the police, and their

agreement with someone else’s decision to call the police. Being a woman and a

conservative also affected the reported likelihood to call the police, whether participants

would call the police, and their agreement with someone else’s decision to call the police.

The overall finding of race not affecting the reported likelihood to call the police,

whether participants would call the police, and their agreement with someone else’s

decision to call the police does not dismiss that future research should still examine and

explore race as a motivation to call the police. News reports continue to demonstrate that

unjust calls are being made to police on black individuals. As these unjust calls continue,

the motivation to call the police should be explored. Racial injustices, discrimination,

biases, and disparities exist; thus, these issues need to be continually studied.

84

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APPENDIX A: AMBIGUOUS RISK SCENARIO

Ambiguous Risk Scenario

It is 11:00 p.m. on a Friday night, and you just got off work. Once you get into

your car to go home you realize you need gas. Before going home, you decide to stop at

your local gas station. While your car begins in fill with gas, you decide to go inside the

gas station for some late-night snacks.

You’re in the back of the store looking at snack options in the freezer section,

when you hear people talking at the counter at the front of the store. The talking gets

louder and you realize the two individuals who were talking begin to yell, and you hear

fists pound on the counter. You decide to take a look at the two people yelling and you

slowly peek around the aisle in which you are hiding, and you see the profile of a young,

*(Black/White)* male.

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APPENDIX B: INFORMED CONSENT

Informed Consent

UNIVERSITY OF NORTHERN IOWA

HUMAN PARTICIPANTS REVIEW INFORMED CONSENT

Project Title: Perceptions of Crime

Name of Investigator(s): Alivia L. Zubrod & Jiuqing Cheng, PhD

Invitation to Participate: You are invited to participate in a research project conducted

through the University of Northern Iowa. The University requires that you give your

agreement to participate in this project. The following information is provided to help

you make an informed decision about whether or not to participate.

Nature and Purpose: This study investigates evaluations and attitudes of a mock crime

summary.

Explanation of Procedures: As a participant in this study, you will be asked to read a

mock crime summary. You will be asked to evaluate the crime scenario and the suspect

presented from the summary. You will also be asked to report your perceptions of risk

and police. In addition, you will be asked to complete demographic attitude questions

and demographic measures. This study is expected to last approximately 20-30 minutes.

You may discontinue involvement in the study at any time.

Discomfort and Risks: There is minimal anticipated risk involved with participating in

this study. You may feel slightly uncomfortable answering some of the questions about

risk perception and your evaluation of the crime summary.

Benefits and Compensation: You will be compensated $1.00 for participating. Your

participation in this study will help us improve our understanding of the public’s

perception of crime.

Confidentiality: All data will be kept confidential; Worker ID’s will be deleted after

completion. Your responses will be encrypted when sent over the internet. Although

your confidentiality will be maintained to the degree permitted by the technology used,

no guarantees can be made regarding the interception of data by third parties when that

data is sent over the internet. Summarized findings with no identifying information may

be published in an academic journal or presented at a scholarly conference. Data with no

IP addresses/other identifiers may also be available for others to view on an open data

site (i.e., open science framework). These data may be used for additional studies.

Right to Refuse or Withdraw: Your participation is voluntary. You are free to

withdraw from participation at any time or to choose not to participate at all, and by

doing so, you will not be penalized or lose benefits to which you are otherwise entitled.

Questions: For questions about the study or desire information in the future regarding

your participation or the study generally, you can contact the project investigators,

Alivia L. Zubrod at [email protected] or the project investigator’s faculty advisor

Jiuqing Cheng, Ph.D. at the Department of Psychology, University of Northern Iowa at

[email protected]. You can also contact the IRB Administrator, University of

Northern Iowa, at [email protected] for questions about rights of research

participants and the participant review process.

Agreement: Registering for the study and clicking on the arrow below indicates that I

98

am fully aware of the nature and extent of my participation in this project as stated

above and the possible risks arising from it. I hereby agree to participate in this project. I

am 17 years of age or older.

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APPENDIX C: DEBRIEFING FORM

Debriefing Form

Thank you for participating in the study entitled “Perceptions of Crime.” As I said

at the beginning, I am examining how people interpret evaluations of a mock crime

scenario. However, within that, I am also looking at if race and severity of risk in

scenario influence more calls to police. For instance, perceiving a high risk or weak risk

scenario the choice to call or not call police might be easy; however, with an ambiguous

scenario (in terms of risk) other factors such as race might provide as a reason to call

police. Your answers regarding your racial attitudes will be coupled with your choice to

call police. If anyone asks you what the study was about, you can honestly say that it was

about evaluations of a mock crime scenario. Please do not mention to others who

complete the study that the study looks at race a well, as that might influence how they

respond.

Worker Code: ZLAERD 3496

If you have any questions about the research protocol, theory, or results, you may

contact the Primary Researcher, Alivia L. Zubrod at [email protected].

Once more, thank you for your participation. We could not do our research

without you!

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APPENDIX D: EVALUATION QUESTIONS

Evaluation Questions

Based on this scenario, what is the likelihood that you would call police?

1 (Not at all likely) (Extremely likely) 10

If someone else saw the same scenario as you and they decided to call the police, what is

the likelihood that calling the police is the correct decision?

1 (Not at all likely) (Extremely likely) 10

To what extent, if any, was the customer at the front of the store dangerous?

1 (Strongly disagree) (Strongly agree) 10

To what extent, if any, do you think the scenario is risky?


To what extent, if any, do you worry that calling the police would bring you trouble?


Based on the scenario you previously read, would you call the police?

Yes

No

If someone else saw the same scenario as you and they decided to call the police, do you

agree or disagree with that choice?

Yes

No

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APPENDIX E: MANIPULATION CHECK

Manipulation Check

What was the race of the customer at the front of the store in the scenario?

Black

White

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APPENDIX F: 30-ITEM DOSPERT SCALE

For each of the following statements, please indicate how risky you perceive each

situation. Provide a rating from Not at all Risky to Extremely Risky, using the

following scale.

Not at all risky – Slightly risky – Somewhat risky – Moderately risky – Risky – Very

risky – Extremely risky

1. Admitting that your tastes are different from those of a friend. (S)

2. Going camping in the wilderness. (R)

3. Betting a day’s income at the horse races. (F/G)

4. Investing 10% of your annual income in a moderate growth diversified fund. (F/I)

5. Drinking heavily at a social function. (H/S)

6. Taking some questionable deductions on your income tax return. (E)

7. Disagreeing with an authority figure on a major issue. (S)

8. Betting a day’s income at a high-stake poker game. (F/G)

9. Having an affair with a married man/woman. (E)

10. Passing off somebody else’s work as your own. (E)

11. Going down a ski run that is beyond your ability. (R)

12. Investing 5% of your annual income in a very speculative stock. (F/I)

13. Going whitewater rafting at high water in the spring. (R)

14. Betting a day’s income on the outcome of a sporting event. (F/G)

15. Engaging in unprotected sex. (H/S)

16. Revealing a friend’s secret to someone else. (E)

17. Driving a car without wearing a seat belt. (H/S)

18. Investing 10% of your annual income in a new business venture. (F/I)

19. Taking a skydiving class. (R)

20. Riding a motorcycle without a helmet. (H/S)

21. Choosing a career that you truly enjoy over a more secure one. (S)

22. Speaking your mind about an unpopular issue in a meeting at work. (S)

23. Sunbathing without sunscreen. (H/S)

24. Bungee jumping off a tall bridge. (R)

25. Piloting a small plane. (R)

26. Walking home alone at night in an unsafe area of town. (H/S)

27. Moving to a city far away from your extended family. (S)

28. Starting a new career in your mid-thirties. (S)

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29. Leaving your young children alone at home while running an errand. (E)

30. Not returning a wallet you found that contains $200. (E)

Note. E = Ethical, F = Financial, H/S = Health/Safety, R = Recreational, and S = Social.

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APPENDIX G: DEMOGRAPHICS

What is your gender identity?

Male

Female

Gender non-binary

Genderfluid

Genderqueer

Prefer not to answer

Not listed: __________________________________________________

What is your age? (Drop down menu)

What is your race/ethnicity? Check all that apply.

o Alaska Native

o American Indian/Native American

o Asian or Asian American

o Black or African American

o Hispanic or Latinx

o Pacific Islander

o White or Caucasian

o Prefer not to answer

o Not listed: __________________________________________________

Are you a US citizen?

Yes

No

What year were you born?

__________________________________________________

What political party do you identify, if any?

Democrat

Republican

Independent

No Affiliation

Not listed: __________________________________________________

How would you describe your...

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Very

Conservative

Conservative Moderate Liberal Very

Liberal

Political

Orientation? o o o o o

Views on

current social

issues?

o o o o o

View on

foreign

policy?

o o o o o

Views on

economics? o o o o o

What is the highest degree or level of school you have completed? If currently enrolled,

mark the previous grade or highest degree received.

Less than high school

High School

Associate’s degree

Bachelor’s degree

Graduate degree

Not listed: _________________________________________________

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APPENDIX H: ADDITIONAL END-OF-STUDY QUESTIONS

Additional End-of-Study Questions

How honest were your answers throughout the study? You will receive payment

regardless of what you answer.

Not honest at all

Slightly honest

Moderately honest

Extremely honest

You will still receive payment, but is there any reason we should not include your data?

__________________________________________________

__________________________________________________

What do you think the current study was about?

__________________________________________________

__________________________________________________

Do you have any comments for the researcher?

__________________________________________________

__________________________________________________

motivation to call police: the exploration of racial and risk averse … · 2020. 4. 24. ·...

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